US20050164270A1 - Methods and system for providing a polymorphism database - Google Patents
Methods and system for providing a polymorphism database Download PDFInfo
- Publication number
- US20050164270A1 US20050164270A1 US11/038,624 US3862405A US2005164270A1 US 20050164270 A1 US20050164270 A1 US 20050164270A1 US 3862405 A US3862405 A US 3862405A US 2005164270 A1 US2005164270 A1 US 2005164270A1
- Authority
- US
- United States
- Prior art keywords
- integer
- analysis
- varchar2
- item
- sequence
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Abandoned
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M1/00—Substation equipment, e.g. for use by subscribers
- H04M1/006—Call diverting means
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
- C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
- C12Q1/6809—Methods for determination or identification of nucleic acids involving differential detection
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
- G16B25/00—ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
- G16B25/30—Microarray design
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
- G16B50/00—ICT programming tools or database systems specially adapted for bioinformatics
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
- G16B25/00—ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M1/00—Substation equipment, e.g. for use by subscribers
- H04M1/72—Mobile telephones; Cordless telephones, i.e. devices for establishing wireless links to base stations without route selection
- H04M1/724—User interfaces specially adapted for cordless or mobile telephones
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M2207/00—Type of exchange or network, i.e. telephonic medium, in which the telephonic communication takes place
- H04M2207/20—Type of exchange or network, i.e. telephonic medium, in which the telephonic communication takes place hybrid systems
- H04M2207/206—Type of exchange or network, i.e. telephonic medium, in which the telephonic communication takes place hybrid systems composed of PSTN and wireless network
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M3/00—Automatic or semi-automatic exchanges
- H04M3/42—Systems providing special services or facilities to subscribers
- H04M3/46—Arrangements for calling a number of substations in a predetermined sequence until an answer is obtained
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M3/00—Automatic or semi-automatic exchanges
- H04M3/42—Systems providing special services or facilities to subscribers
- H04M3/54—Arrangements for diverting calls for one subscriber to another predetermined subscriber
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
- Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10S128/00—Surgery
- Y10S128/92—Computer assisted medical diagnostics
- Y10S128/922—Computer assisted medical diagnostics including image analysis
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
- Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10S707/00—Data processing: database and file management or data structures
- Y10S707/912—Applications of a database
- Y10S707/923—Intellectual property
- Y10S707/924—Patent procedure
- Y10S707/925—Drafting an application
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
- Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10S707/00—Data processing: database and file management or data structures
- Y10S707/953—Organization of data
- Y10S707/955—Object-oriented
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
- Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10S707/00—Data processing: database and file management or data structures
- Y10S707/99931—Database or file accessing
- Y10S707/99933—Query processing, i.e. searching
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
- Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10S707/00—Data processing: database and file management or data structures
- Y10S707/99931—Database or file accessing
- Y10S707/99933—Query processing, i.e. searching
- Y10S707/99934—Query formulation, input preparation, or translation
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
- Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10S707/00—Data processing: database and file management or data structures
- Y10S707/99941—Database schema or data structure
- Y10S707/99944—Object-oriented database structure
- Y10S707/99945—Object-oriented database structure processing
Landscapes
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Physics & Mathematics (AREA)
- Organic Chemistry (AREA)
- General Health & Medical Sciences (AREA)
- Biophysics (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Biotechnology (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Molecular Biology (AREA)
- Theoretical Computer Science (AREA)
- Wood Science & Technology (AREA)
- Zoology (AREA)
- Medical Informatics (AREA)
- Proteomics, Peptides & Aminoacids (AREA)
- Evolutionary Biology (AREA)
- Analytical Chemistry (AREA)
- Genetics & Genomics (AREA)
- Biochemistry (AREA)
- General Engineering & Computer Science (AREA)
- Microbiology (AREA)
- Signal Processing (AREA)
- Immunology (AREA)
- Bioethics (AREA)
- Databases & Information Systems (AREA)
- Apparatus Associated With Microorganisms And Enzymes (AREA)
- Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
- Measuring Pulse, Heart Rate, Blood Pressure Or Blood Flow (AREA)
- Investigating Or Analysing Biological Materials (AREA)
Abstract
Systems and methods for organizing information relating to study of polymorphisms. A database model is provided which interrelates information about one or more of, e.g, subjects from whom samples are extracted, primers used in extracting the DNA from the subjects, about the samples themselves, about experiments done on samples, about particular oligonucleotide probe arrays used to perform experiments, about analysis procedures performed on the samples, and about analysis results. The model is readily translatable into database languages such as SQL. The database model scales to permit storage of information about large numbers of subjects, samples, experiments, chips, etc.
Description
- The present application claims priority from U.S. Prov. App. No. 60/053,842 filed Jul. 25, 1997, entitled COMPREHENSIVE BIO-INFORMATICS DATABASE, from U.S. Prov. App. No. 60/069,198 filed on Dec. 11, 1997, entitled COMPREHENSIVE DATABASE FOR BIOINFORMATICS, and from U.S. Prov. App. No. 60/069,436, entitled GENE EXPRESSION AND EVALUATION SYSTEM, filed on Dec. 11, 1997. The contents of all three provisional applications are herein incorporated by reference.
- The subject matter of the present application is related to the subject matter of the following three co-assigned applications filed on the same day as the present application. GENE EXPRESSION AND EVALUATION SYSTEM (Attorney Docket No. 018547-035010), METHOD AND APPARATUS FOR PROVIDING A BIOINFORMATICS DATABASE (Attorney Docket No. 018547-033810), METHOD AND SYSTEM FOR PROVIDING A PROBE ARRAY CHIP DESIGN DATABASE (Attorney Docket No. 018547-033830). The contents of these three applications are herein incorporated by reference.
- The present invention relates to the collection and storage of information pertaining to chips for processing biological samples and thereby identifying polymorphisms.
- The genomes of all organisms undergo spontaneous mutation in the course of their continuing evolution generating variant forms of progenitor sequences (Gusella, Ann. Rev. Biochem. 55, 831-854 (1986)). The variant form may confer an evolutionary advantage or disadvantage relative to a progenitor form or may be neutral. In some instances, a variant form confers a lethal disadvantage and is not transmitted to subsequent generations of the organism. In other instances, a variant form confers an evolutionary advantage to the species and is eventually incorporated into the DNA of many or most members of the species and effectively becomes the progenitor form. In many instances, both progenitor and variant form(s) survive and co-exist in a species population. The coexistence of multiple forms of a sequence gives rise to polymorphisms.
- Despite the increased amount of nucleotide sequence data being generated in recent years, only a minute proportion of the total repository of polymorphisms in humans and other organisms has so far been identified. The paucity of polymorphisms hitherto identified is due to the large amount of work required for their detection by conventional methods. For example, a conventional approach to identifying polymorphisms might be to sequence the same stretch of oligonucleotides in a population of individuals by dideoxy sequencing. In this type of approach, the amount of work increases in proportion to both the length of sequence and the number of individuals in a population and becomes impractical for large stretches of DNA or large numbers of persons.
- Devices and computer systems for forming and using arrays of materials on a substrate have been developed. These devices and systems have been used for identifying polymorphisms. For example, PCT application WO92/10588, incorporated herein by reference for all purposes, describes techniques for sequencing or sequence checking nucleic acids and other materials. Arrays for performing these operations may be formed in arrays according to the methods of, for example, the pioneering techniques disclosed in U.S. Pat. No. 5,143,854 and U.S. Pat. No. 5,571,639, both incorporated herein by reference for all purposes.
- According to one aspect of the techniques described therein, an array of nucleic acid probes is fabricated at known locations on a chip or substrate. A fluorescently labeled nucleic acid is then brought into contact with the chip and a scanner generates an image file indicating the locations where the labeled nucleic acids bound to the chip. Based upon the identities of the probes at these locations, it becomes possible to extract information such as the identity of polymorphic forms in of DNA or RNA. Such systems have been used to form, for example, arrays of DNA that may be used to study and detect mutations relevant to cystic fibrosis, the P53 gene (relevant to certain cancers), HIV, and other genetic characteristics.
- It would be highly useful to apply such arrays to the study of polymorphisms on a large scale. For example, it would be useful to conduct large scale studies on the correlation between certain polymorphisms and individual characteristics such as susceptibility to diseases and effectiveness of drug treatments. To achieve these benefits, it is contemplated that the operations of chip design, construction, sample preparation, and analysis will occur on a very large scale. The quantity of information related to each of these steps to store and correlate is vast. For large scale polymorphism studies, it will be necessary to store this information in a way to facilitate later advantageous querying and retrieval. What is needed is a system and method suitable for storing and organizing large quantities of information used in conjunction with polymorphism studies.
- The present invention provides systems and methods for organizing information relating to study of polymorphisms. A database model is provided which interrelates information about one or more of, e.g, subjects from whom samples are extracted, primers used in extracting the DNA from the subjects, about the samples themselves, about experiments done on samples, about particular oligonucleotide probe arrays used to perform experiments, about analysis procedures performed on the samples, and about analysis results. The model is readily translatable into database languages such as SQL. The database model scales to permit storage of information about large numbers of subjects, samples, experiments, chips, etc.
- Applications include linkage studies to determine resistance to drugs, susceptibility to diseases, and study of every characteristic of humans and other organisms that is related genetic variability. Another application of a database constructed according to this model is quality control of the various steps of performing a polymorphism study. By preserving information about every step of a polymorphism study, one can assess the reliability of the results or use the preserved information as feedback to improve procedures.
- A further understanding of the nature and advantages of the inventions herein may be realized by reference to the remaining portions of the specification and the attached drawings.
-
FIG. 1 illustrates an overall system and process for forming and analyzing arrays of biological materials such as DNA or RNA. -
FIG. 2A illustrates a computer system suitable for use in conjunction with the overall system ofFIG. 1 . -
FIG. 2B illustrates a computer network suitable for use in conjunction with the overall system ofFIG. 1 . -
FIG. 3 illustrates a key for interpreting a database model. -
FIGS. 4A-4H illustrate a database model for maintaining information for the system and process ofFIG. 1 according to one embodiment of the present invention. - Investigation of Polymorphisms
- A. Preparation of Samples
- Polymorphisms are detected in a target nucleic acid from an individual being analyzed. For assay of genomic DNA, virtually any biological sample (other than pure red blood cells) is suitable. For example, convenient tissue samples include whole blood, semen, saliva, tears, urine, fecal material, sweat, buccal, skin and hair. For assay of cDNA or mRNA, the tissue sample must be obtained from an organ in which the target nucleic acid is expressed. For example, if the target nucleic acid is a cytochrome P450, the liver is a suitable source.
- Many of the methods described below require amplification of DNA from target samples. This can be accomplished by e.g., PCR. See generally PCR Technology: Principles and Applications for DNA Amplification (ed. H. A. Erlich, Freeman Press, NY, N.Y., 1992); PCR Protocols: A Guide to Methods and Applications (eds. Innis, et al., Academic Press, San Diego, Calif., 1990); Mattila et al., Nucleic Acids Res. 19, 4967 (1991); Eckert et al., PCR Methods and
Applications 1, 17 (1991); PCR (eds. McPherson et al., IRL Press, Oxford); and U.S. Pat. No. 4,683,202 (each of which is incorporated by reference for all purposes). - Other suitable amplification methods include the ligase chain reaction (LCR) (see Wu and Wallace, Genomics 4, 560 (1989), Landegren et al., Science 241, 1077 (1988), transcription amplification (Kwoh et al., Proc. Natl. Acad. Sci. USA 86, 1173 (1989)), and self-sustained sequence replication (Guatelli et al., Proc. Nat. Acad. Sci. USA, 87, 1874 (1990)) and nucleic acid based sequence amplification (NASBA). The latter two amplification methods involve isothermal reactions based on isothermal transcription, which produce both single stranded RNA (ssRNA) and double stranded DNA (dsDNA) as the amplification products in a ratio of about 30 or 100 to 1, respectively.
- B. Detection of Polymorphisms in Target DNA
- There are two distinct types of analysis depending whether a polymorphism in question has already been characterized. The first type of analysis is sometimes referred to as de novo characterization. This analysis compares target sequences in different individuals to identify points of variation, i.e., polymorphic sites. By analyzing groups of individuals representing the greatest ethnic diversity among humans and greatest breed and species variety in plants and animals, patterns characteristic of the most common alleles/haplotypes of the locus can be identified, and the frequencies of such populations in the population determined. Additional allelic frequencies can be determined for subpopulations characterized by criteria such as geography, race, or gender. The second type of analysis is determining which form(s) of a characterized polymorphism are present in individuals under test. There are a variety of suitable procedures, which are discussed in turn.
- 1. Allele-Specific Probes
- The design and use of allele-specific probes for analyzing polymorphisms is described by e.g., Saiki et al.,
Nature 324, 163-166 (1986); Dattagupta, EP 235,726, Saiki, WO 89/11548. Allele-specific probes can be designed that hybridize to a segment of target DNA from one individual but do not hybridize to the corresponding segment from another individual due to the presence of different polymorphic forms in the respective segments from the two individuals. Hybridization conditions should be sufficiently stringent that there is a significant difference in hybridization intensity between alleles, and preferably an essentially binary response, whereby a probe hybridizes to only one of the alleles. Some probes are designed to hybridize to a segment of target DNA such that the polymorphic site aligns with a central position (e.g., in a 15 mer at the 7 position; in a 16 mer, at either the 8 or 9 position) of the probe. This design of probe achieves good discrimination in hybridization between different allelic forms. - Allele-specific probes are often used in pairs, one member of a pair showing a perfect match to a reference form of a target sequence and the other member showing a perfect match to a variant form. Several pairs of probes can then be immobilized on the same support for simultaneous analysis of multiple polymorphisms within the same target sequence.
- 2. Tiling Arrays
- The polymorphisms can also be identified by hybridization to nucleic acid arrays, some example of which are described by WO 95/11995 (incorporated by reference in its entirety for all purposes). WO 95/11995 also describes subarrays that are optimized for detection of a variant forms of a precharacterized polymorphism. Such a subarray contains probes designed to be complementary to a second reference sequence, which is an allelic variant of the first reference sequence. The second group of probes is designed by the same principles as described in the Examples except that the probes exhibit complementarily to the second reference sequence. The inclusion of a second group (or further groups) can be particular useful for analyzing short subsequences of the primary reference sequence in which multiple mutations are expected to occur within a short distance commensurate with the length of the probes (i.e., two or more mutations within 9 to 21 bases).
- 3. Allele-Specific Primers
- An allele-specific primer hybridizes to a site on target DNA overlapping a polymorphism and only primes amplification of an allelic form to which the primer exhibits perfect complementarily. See Gibbs, Nucleic Acid Res. 17, 2427-2448 (1989). This primer is used in conjunction with a second primer which hybridizes at a distal site. Amplification proceeds from the two primers leading to a detectable product signifying the particular allelic form is present. A control is usually performed with a second pair of primers, one of which shows a single base mismatch at the polymorphic site and the other of which exhibits perfect complementarily to a distal site. The single-base mismatch prevents amplification and no detectable product is formed. The method works best when the mismatch is included in the 3′-most position of the oligonucleotide aligned with the polymorphism because this position is most destabilizing to elongation from the primer. See, e.g., WO 93/22456.
- 4. Direct-Sequencing
- The direct analysis of the sequence of polymorphisms of the present invention can be accomplished using either the dideoxy chain termination method or the Maxam Gilbert method (see Sambrook et al., Molecular Cloning, A Laboratory Manual (2nd Ed., CSHP, New York 1989); Zyskind et al., Recombinant DNA Laboratory Manual, (Acad. Press, 1988)).
- 5. Denaturing Gradient Gel Electrophoresis
- Amplification products generated using the polymerase chain reaction can be analyzed by the use of denaturing gradient gel electrophoresis. Different alleles can be identified based on the different sequence-dependent melting properties and electrophoretic migration of DNA in solution. Erlich, ed., PCR Technology, Principles and Applications for DNA Anplification, (W.H. Freeman and Co, New York, 1992), Chapter 7.
- 6. Single-Strand Conformation Polymorphism Analysis
- Alleles of target sequences can be differentiated using single-strand conformation polymorphism analysis, which identifies base differences by alteration in electrophoretic migration of single stranded PCR products, as described in Orita et al., Proc. Nat. Acad. Sci. 86, 2766-2770 (1989). Amplified PCR products can be generated as described above, and heated or otherwise denatured, to form single stranded amplification products. Single-stranded nucleic acids may refold or form secondary structures which are partially dependent on the base sequence. The different electrophoretic mobilities of single-stranded amplification products can be related to base-sequence difference between alleles of target sequences.
- Biological Material Analysis System
- One embodiment of the present invention operates in the context of a system for analyzing biological or other materials using arrays that themselves include probes that may be made of biological materials such as RNA or DNA. The VLSIPS™ and GeneChip™ technologies provide methods of making and using very large arrays of polymers, such as nucleic acids, on chips. See U.S. Pat. No. 5,143,854 and PCT Patent Publication Nos. WO 90/15070 and 92/10092, each of which is hereby incorporated by reference for all purposes. Nucleic acid probes on the chip are used to detect complementary nucleic acid sequences in a sample nucleic acid of interest (the “target” nucleic acid).
-
FIG. 1 illustrates anoverall system 100 for forming and analyzing arrays of biological materials such as RNA or DNA. A part ofsystem 100 is apolymorphism database 102.Polymorphism database 102 includes information about, e.g., biological sources, preparation of samples, design of arrays, raw data obtained from applying experiments to chips, analysis procedures applied, and analysis results, etc.Polymorphism database 102 facilitates large scale study of polymorphisms. - A chip design system 104 is used to design arrays of polymers such as biological polymers such as RNA or DNA. Chip design system 104 may be, for example, an appropriately programmed Sun Workstation or personal computer or workstation, such as an IBM PC equivalent, including appropriate memory and a CPU. Chip design system 104 obtains inputs from a user regarding chip design objectives including polymorphisms of interest, and other inputs regarding the desired features of the array. Optionally, chip design system 104 from external databases such as GenBank. The output of chip design system 104 is a set of chip design computer files in the form of, for example, a switch matrix, as described in PCT application WO 92/10092, and other associated computer files. The chip design computer files form a part of
polymorphism database 102. Systems for designing chips for study of polymorphisms are disclosed in U.S. Pat. No. 5,571,639 and in PCT application WO 95/11995, the contents of which are herein incorporated by reference. - The chip design files are input to a mask design system (not shown) that designs the lithographic masks used in the fabrication of arrays of molecules such as DNA. The mask design system designs the lithographic masks used in the fabrication of probe arrays. The mask design system generates mask design files that are then used by a mask construction system (not shown) to construct masks or other synthesis patterns such as chrome-on-glass masks for use in the fabrication of polymer arrays.
- The masks are used in a synthesis system (not shown). The synthesis system includes the necessary hardware and software used to fabricate arrays of polymers on a substrate or chip. The synthesis system includes a light source and a chemical flow cell on which the substrate or chip is placed. A mask is placed between the light source and the substrate/chip, and the two are translated relative to each other at appropriate times for deprotection of selected regions of the chip. Selected chemical reagents are directed through the flow cell for coupling to deprotected regions, as well as for washing and other operations. The substrates fabricated by the synthesis system are optionally diced into smaller chips. The output of the synthesis system is a chip ready for application of a target sample.
- Information about the mask design, mask construction, and probe array synthesis is presented by way of background. A
biological source 112 is, for example, tissue from a plant or animal. Various processing steps are applied to material frombiological source 112 by asample preparation system 114. Operation ofsample preparation system 114 in the context of a polymorphism study is discussed below in further detail. - The prepared samples include nucleic acid sequences such as DNA. When the sample is applied to the chip by a
sample exposure system 116, the nucleic acids may or may not bond to the probes. The nucleic acids can be tagged with fluoroscein labels to determine which probes have bonded to nucleotide sequences from the sample. The prepared samples will be placed in ascanning system 118.Scanning system 118 includes a detection device such as a confocal microscope or CCD (charge-coupled device) that is used to detect the location where labeled receptors have bound to the substrate. The output ofscanning system 118 is an image file(s) indicating, in the case of fluorescein labeled receptor, the fluorescence intensity (photon counts or other related measurements, such as voltage) as a function of position on the substrate. These image files may also form a part ofpolymorphism database 102. Since higher photon counts will be observed where the labeled nucleic acid(s) has bound more strongly to the array of probes, and since the monomer sequence of the probes on the substrate is known as a function of position, it becomes possible to analize the sequence(s) of the nucleic acid(s) that are complementary to the probes. - The image files and the design of the chips are input to an
analysis system 120 that, e.g., calls bases. Such analysis techniques are described in EPO Pub. No. 0717113A, the contents of which are herein incorporated by reference. - Chip design system 104,
analysis system 120 and control portions ofexposure system 116,sample preparation system 114, andscanning system 118 may be appropriately programmed computers such as a Sun workstation or IBM-compatible PC. An independent computer for each system may perform the computer-implemented functions of these systems or one computer may combine the computerized functions of two or more systems. One or more computers may maintainchip design database 102 independent of the computers operating the systems ofFIG. 1 orchip design database 102 may be fully or partially maintained by these computers. -
FIG. 2A depicts a block diagram of ahost computer system 10 suitable for implementing the present invention.Host computer system 210 includes abus 212 which interconnects major subsystems such as acentral processor 214, a system memory 216 (typically RAM), an input/output (I/O)adapter 218, an external device such as adisplay screen 224 via adisplay adapter 226, akeyboard 232 and amouse 234 via an I/O adapter 218, a SCSI host adapter 236, and afloppy disk drive 238 operative to receive afloppy disk 240. SCSI host adapter 236 may act as a storage interface to a fixeddisk drive 242 or a CD-ROM player 244 operative to receive a CD-ROM 246.Fixed disk 244 may be a part ofhost computer system 210 or may be separate and accessed through other interface systems. Anetwork interface 248 may provide a direct connection to a remote server via a telephone link or to the Internet.Network interface 248 may also connect to a local area network (LAN) or other network interconnecting many computer systems. Many other devices or subsystems (not shown) may be connected in a similar manner. - Also, it is not necessary for all of the devices shown in
FIG. 2A to be present to practice the present invention, as discussed below. The devices and subsystems may be interconnected in different ways from that shown inFIG. 2A . The operation of a computer system such as that shown inFIG. 2A is readily known in the art and is not discussed in detail in this application. Code to implement the present invention, may be operably disposed or stored in computer-readable storage media such assystem memory 216, fixeddisk 242, CD-ROM 246, orfloppy disk 240. -
FIG. 2B depicts anetwork 260 interconnectingmultiple computer systems 210.Network 260 may be a local area network (LAN), wide area network (WAN), etc.Bioinformatics database 102 and the computer-related operations of the other elements ofFIG. 2B may be divided amongstcomputer systems 210 in any way withnetwork 260 being used to communicate information among the various computers. Portable storage media such as floppy disks may be used to carry information between computers instead ofnetwork 260. - Overall Description of Database
-
Polymorphism database 102 is preferably a relational database with a complex internal structure. The structure and contents ofchip design database 102 will be described with reference to a logical model depicted inFIGS. 4A-4H that describes the contents of tables of the database as well as interrelationships among the tables. A visual depiction of this model will be an Entity Relationship Diagram (ERD) which includes entities, relationships, and attributes. A detailed discussion of ERDs is found in “ERwin version 3.0 Methods Guide” available from Logic Works, Inc. of Princeton, N.J., the contents of which are herein incorporated by reference. Those of skill in the art will appreciate that automated tools such as Developer 2000 available from Oracle will convert the ERD fromFIGS. 4A-4H directly into executable code such as SQL code for creating and operating the database. -
FIG. 3 is a key to the ERD that will be used to describe the contents ofchip design database 102. A representative table 302 includes one or morekey attributes 304 and one or more non-key attributes 306. Representative table 302 includes one or more records where each record includes fields corresponding to the listed attributes. The contents of the key fields taken together identify an individual record. In the ERD, each table is represented by a rectangle divided by a horizontal line. The fields or attributes above the line are key while the fields or attributes below the line are non-key. An identifyingrelationship 308 signifies that the key attribute of a parent table 310 is also a key attribute of a child table 312. Anon-identifying relationship 314 signifies that the key attribute of a parent table 316 is also a non-key attribute of a child table 318. Where (FK) appears in parenthesis, it indicates that an attribute of one table is a key attribute of another table. Both the depicted non-identifying and identifying relationship are one to one-or-more relationships where one record in the parent table corresponds to one or more records in the child table. Analternative non-identifying relationship 324 is a one to zero-or-more relationship where one record in a parent table 320 corresponds to zero or more records in a child table 322. - Database Model
-
FIGS. 4A-4H are entity relationship diagrams (ERDs) showing elements ofpolymorphism database 102 according to one embodiment of the present invention. Each rectangle in the diagram corresponds to a table indatabase 102. First, the relationships and general contents of the various tables will be described. - The interrelationships and general contents of the tables of
database 102 will be described first. Then a chart will be presented listing and describing all of the fields of the various tables. -
FIG. 4A illustrates core elements ofdatabase 102 according to one embodiment of the present invention. A subject table 402 lists organisms from which samples have been extracted for polymorphism analysis or other tissue sources. Samples may also be obtained from tissue collections not associated with any one identified organism. Information stored within subject table 402 includes the name, gender, family, position with family, (e.g., father, mother, etc.), and ethnic group. For human subjects, the name and family will preferably be represented in coded form to assure privacy. Associated with each subject is a species as listed in a species table 404. Also, a relationship may be defined among subjects a subject relationship table 406 which includes records corresponding to related subjects. These relationships may be father-mother, sibling, twins, etc. Subjects may be part of a group that is being studied, e.g., a group with a congenital disease, or a toxic reaction to a particular drug. The groups are listed in a subject group table 408. Participation of subjects in groups is defined by a subject participation table 410 which lists all group memberships. - Samples and their attributes are listed in a sample table 412. Each sample has an associated sample type. The sample types are listed in a sample type table 414. Possible sample types include blood, urine, etc. Companies or institutions that provide samples are listed in a sample source table 416.
-
Database 102 provides an item table 418 that includes records for items. There are various types of items that correspond to different stages of the sample preparation process. An “item derivation” transforms an item of one type into an item of another type. The following table lists various item types and item derivation types for a representative embodiment.by Item Item Type Derived from Derivation Type Sample other samples pooling Sample other sample splitting Extracted DNA Sample DNA Extraction Target (Sequences Extracted DNA PCR of interest amplified) Fluorescently Target Labeling Labeled Target Hybridized Chip Labeled Target Hybridization (application of target to chip) Stained Hybridized Hybridized Chip Staining Chip
Item derivations are listed in an item derivation table 420. It should be noted that derivations need not produce a change between item types. Each item derivation occurs in accordance with a protocol that characterizes the step or steps in the derivation. Protocols are listed in a protocol table 428. Each item derivation is performed by an employee listed in employee table 432. - Unused chips are listed in a chip table 422. Hybridized chips (i.e., chips that have had target applied) are listed in a hybridized chip table 424. A hybridized sample map table 426 lists the relationships between hybridized chips and the samples that have been applied to them.
- Stained hybridized chips are scanned in a process referred to here as a scan experiment. Scan experiments are listed in a scan experiment table 430. The scan experiment occurs in accordance with a protocol listed in protocol table 428. The scan experiment is performed by an employee listed in employee table 432.
-
FIG. 4B depicts further details of the data model for items and item derivations. The various item types are listed in an item type table 434 and the various item derivation types are listed in an item derivation type table 436. The relationships between successive item types, e.g., sample and target are defined in an item type derivation table 438. An item has associated attributes. For example, for a target,database 102 may store the concentration, volume, location and/or remaining amount. All item attributes are stored in an item attribute table 440. Item attributes may be shared among multiple items. For example, a series of targets may all share a preparation date. An item attribute item map table 442 implements a many-to-many relationship between item attributes and items. The various types of item attributes such as preparer, preparation date, etc. are listed in an item attribute type table 444. Each item type has corresponding attribute types. Some attribute types are, however, shared among various item types. Accordingly, there is a many-to-many relationship among item attribute types and item types that is implemented by an item type map table 446. - The tables of
FIG. 4B represent a powerfully general model of the sample preparation process. Changes in process steps that require changes in the type of information that should be stored may be implemented by changing and adding table contents rather than providing new tables or changing relationships among tables. -
FIG. 4C depicts a detailed data model for storing information about protocols according to the present invention. Protocols as stored in protocol table 428 represent information about particular processes that have been performed including item derivations, analyses, and scan experiments. Each protocol has an associated protocol template. Protocol templates identify protocol types. For example, one protocol template may be a PCR template. All protocols associated with the PCR template identify parameters for performing a PCR procedure. Protocol templates are listed in a protocol template table 448. A parameter table 450 lists all the parameters and their values for all the protocols listed in protocol table 428. A parameter template table 452 lists the various parameter types along with default values. An examples of a parameter template would be a PCR reaction temperature. The parameter template would include a default value for this parameter. Parameter table 450 might then list many different PCR reaction temperature values that would be used by many different protocols. If a parameter value has not been modified by the user, it inherits the standard value of the associated parameter template. A parameter template set is a set of parameter templates that are used for a particular purpose, e.g., in association with protocols according to one or more protocol templates. Parameter template sets are listed in a parameter template set table 454. There are different types of parameter template set and these are listed in a parameter template set table 456. A mapping between parameter template sets and protocol templates is defined by a protocol template set map table 458. - Protocol templates may have associated lengthy verbal information about how to perform protocol steps. A protocol template document table 460 stores references to documents that include instructions for performing protocols.
- As with the items, the data model for protocols defined by
FIG. 4C is highly general and allows significant changes in the way item derivations, analyses, and experiments are performed without changing the underlying data model. - Referring again to
FIG. 4A , there are tables to record information concerning the use of primers in PCR. A fragment table 462 lists all the sequence fragments investigated in conjunction withdatabase 102. Associated with each fragment are one or more primer pairs used to amplify the fragment in a PCR process. A primer pair table 464 lists all the primer pairs including information about whether the primer pair actually worked to amplify the fragment. In order to develop the information about the effectiveness of primer pairs, there is a PCR table 466 that lists records identifying the outcome of multiple PCR operations. The individual PCR operations are identified by reference to item derivation table 420. - A single PCR operation may be used to amplify many different fragments and thus employ many different primer pairs. Of course, a single primer pair may be used in multiple PCR operations. There is therefore a many-to-many relationship between PCR operations and primer pairs that is recorded by a primer pair PCR map table 468.
- Information about individual primers is stored in a primer table 470. Also, each primer has an associated protocol in protocol table 428 that characterizes the primer preparation process. Information about primer orders is listed in a primer order table 472. Each primer order is to a vendor and the vendors are listed in a vendor table 474. Each primer order is made by an employee listed in employee table 432. A primer order design map table 476 implements a many-to-many relationship between primer orders and primers.
- The data model described here thus preserves information about primers used in PCR reactions. One can improve results by using primers that have successfully amplified a given fragment in the past. Sometimes particular groups of primer pairs cannot be multiplexed together in the same PCR process. The information preserved here thus permits experimenters to make optimal use of expensive and time consuming PCR procedures.
- It is also useful to preserve information about the chip production process and the origin of individual chips. A wafer table 478 lists wafers. When chips are produced, many chips are produced at the same time as part of a single wafer. Chip table 422 stores references to wafer table 478 for each chip and the location of each chip on its wafer at production time. Sometimes there is analytic significance associated with the location of a chip on the wafer. Each wafer is produced as part of a lot and the identify of the lot for each wafer is recorded by wafer table 478 as a reference to a lot table 480 that lists each lot.
-
FIG. 4D depicts further details of tables pertaining to chip design that are preferably maintained withinpolymorphism database 102 according to one embodiment of the present invention. A tiling design table 482 lists tiling designs. Each tiling design represents the application of a particular tiling format to a sequence to be investigated. Tiling formats indicate probe orientation, probe length, and the position within a probe of a single nucleotide polymorphism being investigated. In a preferred embodiment, there may be very few tiling formats and they are listed in a tiling format table 484. - A particular tiling design includes many atom designs specifying the design of a single atom. In one embodiment, an atom is a group of typically four probes used to investigate a single base position with each probe hybridizing to a sequence including a different base at that position. Atom designs are listed in an atom design table 486. Records identifying the designs of individual probes are listed in a probe design table 488. A probe design role table 490 indicates the roles of probes listed in probe design table 488 in the atom designs of atom design table 486. For combinations of probe design and atom design, probe design role table 490 indicates which base the probe hybridizes to at the substitution position and whether the probe represents a match or a mismatch to the wild type.
- A probe data table 492 gives the hybridization intensity values for particular probes designs as determined in particular scan experiments. Each record of the table also gives the number of pixels used to determine the intensity value and the standard deviation of intensity as measured among the pixels.
-
FIGS. 4E-4G depict aspects ofpolymorphism database 102 related to analysis procedures and their results according to one embodiment of the present invention. An analysis table 494 lists analyses performed. An analysis generally refers to a non-trivial transformation of data. Records of analysis table 494 include references to protocol table 428 to specify parameters used for each analysis. Analyses may take as their input raw data or the results of previous analyses. An analysis dependency table 496 lists dependencies among analyses where one analysis depends on the data developed by another analysis. An analysis input table 498 lists inputs for analyses listed in analysis table 494. - On the right side of
FIG. 4E are various tables used to support analyses. A chip design sequence map table 500 correlates particular fragments with chip designs. A sequence position table 502 lists investigated sequence positions indicating their positions on a fragment. Records of sequence position table 502 reference a genomic sequence position table 504 which gives sequence positions in the genome rather than within individual fragments. - A scan experiment set table 506 lists sets of scan experiments. This allows for groupings of experiments for individuals or populations to serve as the basis for polymorphism analysis. A scan experiment used table 508 lists records indicating memberships of a scan experiment in a scan experiment set.
- A tiling data table 510 lists records identifying tiling designs as implemented in particular chips measured by particular scan experiments. An atom data table 512 lists the intensities measured for particular sequence positions as measured in scan experiments identified by the tiling data records. A subject sequence position data table 514 lists combinations of sequence position and scan experiment.
- A series of tables in
FIGS. 4E-4G correspond to different types of analysis that occur during the course of a polymorphism investigation. The types presented here are merely representative. A parallel series of tables provide the analysis results. A polymorphism analysis table 516 lists references to analysis table 494. The results of the performed polymorphism analyses are listed in a polymorphism position result table 518. A record of this table gives a result for a polymorphism analysis for a particular position as determined based on a particular set of scan experiments. In one embodiment the result is whether a particular mutation is certain, likely, possible, or not possible at the position. The result may also be that the reference is wrong. - A user polymorphism analysis table 520 lists user interpretations of results as listed in polymorphism position result table 518. The records of user polymorphism analysis table 520 are references to analysis table 494. The user interpretations themselves are stored in a user polymorphism analysis result table 522. Each result is a likelihood of a particular mutation at a position as considered by a user plus an accompanying user comment.
- A P-Hat analysis estimates the relative concentrations of wild type sequence and sequence having a particular mutation as determined in a particular scan experiment. A P-Hat analysis table 524 lists references to analysis table 494. An atom result table 526 gives estimates of the relative concentration along with upper and lower bounds and a maximum intensity. For heterozygous mutations, the estimates of relative concentration will cluster around 0.5 For homozygous mutations, the estimates should cluster around 1.0.
- Base call analyses are determinations of the base at a particular position for a particular individual that may be based on more than one experiments. A base call analysis table 528 lists references to analysis table 494. A base call result table 530 lists the called bases for particular combinations of sequence position and subject.
- A P-Hat grouping analysis determines a measure of likelihood that data in a set of scan experiments results from separate genotypes. P-hat grouping analyses are listed in a p-hat grouping analysis table 532 by reference to analysis table 494. P-hat grouping analysis results are listed in a mutation fraction result table 534. A group separation is given for various combinations of sequence position and scan experiment set.
- A clustering analysis determines an alternative measure of likelihood that data in a set of scan experiments results from separate genotypes. Clustering analyses are listed in a clustering analysis table 536 by reference to analysis table 494. Clustering analysis results are listed in a clustering result table 538. A clustering factor is given for various combinations of sequence position and scan experiment set.
-
FIG. 4F shows tables which support normalization and footprint finding operations that support the analyses referred to inFIG. 4E . Hybridization intensity measurements made in scan experiments should be normalized over a set of scan experiments. The normalization should take into account differences in amplification level produced by different PCR processes. - Normalization is done by region of sequence. A normalization region analysis determines the boundaries of a region to be normalized. The determination of boundaries takes into account that different fragments of sequence are amplified by different PCR procedures. A normalization region analysis table 540 lists normalization region analyses by reference to analysis table 494. A normalization region result table 542 lists the boundaries for each determined normalization region.
- Normalization values for identified normalization regions are themselves determined by normalization analyses. Normalization analyses are listed in a normalization analysis table 544 by reference to analysis table 494. A normalization result table 546 lists the normalization values for regions.
- A footprint analysis determines regions of sequence for which the hybridization intensity is elevated for the purposes of quality control. Footprint analyses are listed in a footprint analysis table 548 by reference to analysis table 494. Footprints are identified by sequence starting point and ending point in a particular scan experiment in a footprint table 550.
-
FIG. 4G depicts tables pertaining to measurement quality according to one embodiment of the present invention. A tiling data quality analysis determines the quality of results from a scan experiment. These analyses are listed in a tiling data quality analysis table 552 by reference to analysis table 494. Tiling data quality analysis results are listed in a tiling data quality result table 554. The results include an average hybridization intensity value for perfect match or mismatch probes. A wild type call rate gives the fraction of atom data where the probe corresponding to the reference base has the highest hybridization intensity. A wild type call rate of around 1.0 indicates good quality. Where the call rate is less than 0.75, the scan experiment should be rejected. An accept data field indicates whether the analysis indicates rejection or acceptance. - Where scan experiment measurements indicate two or more non-wild type bases within a probe length, this indicates a measurement problem for the affected region of sequence. These regions are identified by difficult region analyses listed in a difficult region analysis table 556 by reference to analysis table 494. A difficult region result table 558 lists the regions identified as being difficult.
- Analysis dependency table 496 indicates interrelationships among the various analyses of
FIGS. 4E-4G . A footprint analysis may depend on a normalization analysis which may in turn depend on a normalization region analysis. A basecall analysis or PHatGrouping analysis may depend on an atom analysis. A polymorphism analysis may depend on any of these analyses and/or a user polymorphism analysis and/or a clustering analysis. - Another aspect of the investigation of polymorphisms is seeking patent protection for identified polymorphisms.
FIG. 4H shows tables ofpolymorphism database 102 related to efforts to seek patent protection according to one embodiment of the present invention. A polymorphism patent sequence table 560 lists sequences for which patent protection is sought. A patent application table 562 lists patent applications directed toward the protection of polymorphisms. A polymer patent application sequence map table 564 implements a many-to-many relationship between patent applications and sequences. A prior application table 566 lists relationships between patent applications and prior related patent applications. An attorney table 568 lists attorneys responsible for preparing patent applications listed in patent application table 562. A law firm table 570 lists the law firms to which the attorneys listed in attorney table 568 belong. - An employee group table 572 lists groups of inventors for the patent applications listed in table 562. Individual inventors are listed in employee table 432. An employee group map table 574 implements a many-to-many relationship between inventors and groups of inventors.
- The data model of
FIG. 4H greatly facilitates the process of securing patent protection for polymorphisms and thereby increases the commercial incentive for investigation of polymorphisms. - Database Contents
- The contents of the tables introduced above will now be presented in greater detail in the following chart.
TABLE FIELD COMMENT tblSubject SubjectId: INTEGER Identifies biological source of sample. SpeciesID: INTEGER Species of subject. Name: VARCHAR2(20) Name of subject (anonimized for human subjects). Gender: VARCHAR2(10) Gender of subject. Family: VARCHAR2(20) Family of subject (anonimized for human subjects). Member: SMALLINT Position in family (father, mother, etc.). Group: VARCHAR2(20) Ethnic group. CellLineID: VARCHAR2(20) Identifier for sample source not associated with particular organism. IsReference: SMALLINT Whether or not subject is in a group. tblSpecies SpeciesId: INTEGER Species identifier. Name: VARCHAR2(30) Name of species. SubjectRelationship Subject1: INTEGER First subject in relationship. Subject2: INTEGER Second subject in relationship. Position: VARCHAR2(2) Nature of relationship. tblSubjectGroup GroupId: INTEGER Identifier of group of subjects (not same as ethnic group). GroupCode: VARCHAR2(20) Code identifier for group. Comments: LONG VARCHAR User comments on group. upsize_ts: DATE Creation date for group. tblSubjectParticipation SubjectId: INTEGER Reference to subject table. GroupId: INTEGER Reference to subject group table. tblSample SampleId: INTEGER Sample identifier. SubjectID: INTEGER Reference to subject table. SampleSourceId: CHAR(18) Institutional source of sample. Code: VARCHAR2(20) Code representing individual subject. Recipient: VARCHAR2(20) Person accepting sample. Provider: VARCHAR2(20) Person or institution providing sample. DateReceived: DATE Date sample received. ProtocolId: INTEGER Reference to protocol table. SampleTypeId: INTEGER Reference to sample type table. tblSampleType SampleTypeId: INTEGER Sample type identifier. Description: VARCHAR2(50) Description of sample type. tblSample Source SampleSourceId: CHAR(18) Identifier of institutional sample source. ProviderName: VARCHAR2(20) Name of individual or institutional sample provider. Item ItemId: INTEGER Item identifier. ItemTypeId: INTEGER Item type identifier. ItemName: VARCHAR2(50) Name of item. ItemDerivation Item1Id: INTEGER Derivation source. Item2Id: INTEGER Derivation result. EmployeeId: INTEGER Employee responsible for derivation. DerivationTypeId: INTEGER Derivation type identifier. Protocolid: VARCHAR2(18) Reference to protocol table. Date: DATE Date of derivation. tblChip ChipId: INTEGER Rename reference to item table. ChipDesignPlacementId: INTEGER Placement on wafer. LocationId: INTEGER Location of chip. WaferId: INTEGER Wafer the chip was on. tblHybedChip HybedChipId: INTEGER Rename reference to item table. SubjectID: INTEGER Reference to subject table. ProtocolId: INTEGER Reference to protocol table. Repetition: SMALLINT Refers to number of times chip has been washed and reused. tblHybSampleMap ItemId: INTEGER Reference to item table. Protocol ProtocolId: INTEGER Protocol identifier. ProtocolTemplateId: INTEGER Protocol template identifier. Name: VARCHAR2(100) Name of protocol. tblScanExperiment ScanExptId: INTEGER Scan experiment identifier. ItemId: INTEGER Reference to item table. ScanCode: VARCHAR2(25) File for scan results. ProtocolId: INTEGERP Reference to protocol table. ScanRatingId: INTEGER Assessment of scan quality. ExperimenterId: INTEGER Experimenter identifier. Date: DATE Date of experiment. ConversionTool: VARCHAR2(50) Program used to convert from scan image to intensities. ConversionDate: DATE Date of conversion. ScanStatus: VARCHAR2(50) whether or not scan image has been converted to intensities Comments: LONG VARCHAR Comments. Employee EmployeeId: INTEGER Employee identifier. EmployeeCode: VARCHAR2(5) Code for employee FName: VARCHAR2(20) First name of employee. MName: VARCHAR2(20) Middle name of employee. LName: VARCHAR2(20) Last name of employee. ItemType ItemId: INTEGER Item type identifier. ItemTypeName: VARCHAR2(30) Name of item type. FormName: VARCHAR2(100) Reference to user interface form for item type. ItemDerivationType DerivationTypeId: INTEGER Derivation type identifier. DerivationType: VARCHAR2(50) Description of derivation type. ItemTypeDerivation NextItemTypeId: INTEGER Result type of derivation. ItemTypeId: INTEGER Source type of derivation. ItemAttribute itemAttributeId: INTEGER Item attribute identifier. ItemAttributeTypeId: INTEGER Reference to item attribute type table. Attribute: VARCHAR2(50) Attribute value. ItemAttributeItemMap ItemAttributeId: INGEGER Reference to item attribute table. ItemId: INTEGER Reference to item table. ItemAttributeType ItemAttributetypeId: INTEGER Item attribute identifier. ItemAttributeName: VARCHAR2(30) Name of item attribute type. ItemTypeMap ItemAttributeTypeId: INTEGER Reference to item attribute type table. ItemTypeId: INTEGER Reference to item type table. ProtocolTemplate ProtocolTemplateId: INTEGER Protocol template identifier. Name: VARCHAR2(100) Name of protocol template. DateCreated: DATE Date protocol template created. FormName: VARCHAR2(50) Name of the electronic form used for protocol template. Parameter ParameterId: INTEGER Parameter identifier. ParameterTemplateId: INTEGER Reference to parameter template table. Value: VARCHAR2(20) Value of parameter. ProtocolID: INTEGER Reference to protocol table. ParameterTemplate ParameterTemplateId: INTEGER Parameter template identifier. Name: VARCHAR2(100) Name of parameter template. ParamTemplateSetId: INTEGER Reference to parameter template set table. StandardValue: VARCHAR2(100) Default value for parameter. ParamTemplateSet ParamTemplateSetId: INTEGER Parameter template set identifier. TypeId: INTEGER Renamed reference to parameter template set type table. Name: VARCHAR2(20) Name of parameter template set. ParamTemplateSetType ParamTempSetTypeId: INTEGER Parameter template set type identifier. Description: VARCHAR2(50) Description of parameter template set type. ParameterTemplateSetMap ProtocolTemplateId: INTEGER Reference to protocol template table. ParamTemplateSetId: INTEGER Reference to parameter template set table. ProtocolTemplateDoc ProtocolDocId: INTEGER Protocol Template document identifier. ProtocolTemplateId: INTEGER Reference to protcol template table. Name: VARCHAR2(100) Name of protocol template. PathAndFileName: VARCHAR2(50) File name for protocol template document. AuthorName: INTEGER Author of protocol template document. CreationDate: DATE Creation date of protocol template document. tbFragment FragmentId: INTEGER Fragment identifier. ChipSequence: LONG VARCHAR Sequence of fragment. Code: VARCHAR2(50) Code representing fragment. tblPrimerPair PrimerPairId: INTEGER Identifier for primer pair. LeftPrimerId: INTEGER Left primer identifier. RightPrimerId: INTEGER Right primer identifier. PCRSize: INTEGER length of amplified fragment Worked: SMALLINT Whether or not pair successfully amplified fragment. FragmentId: INTEGER Reference to fragment table. tblPCR Item1Id: INTEGER First part of reference to item derivation table. Item2Id: INTEGER Second part of reference to item derivation table. Reactionworked: SMALLINT Whether or not PCR reaction worked. PrimePairPCRMap PrimerPairId: INTEGER Reference to primer pair table. Item1ID: INTEGER First part of referenced item derivation table. Item2Id: INTEGER Second part of referenced item derivation table. tblPrimer PrimerId: INTEGER Primer identifier. ProtocolId: INTEGER Reference to protocol table. OligoSeq: VARCHAR2(35) Sequence of primer. Position: INTEGER Position of primer on fragment. Length: INTEGER Length of primer. MeltingTemp: INTEGER Melting temperature of primer. Direction: VARCHAR2(20) Direction (forward or reverse). tblPrimerOrder OrderId: INTEGER Order identifier. EmployeeId: INTEGER Employee who made order. VendorId: INTEGER Vendor for order. OrderDate: DATE Date of order. Owner: VARCHAR2(50) Name of employee making order. Vendor: VARCHAR2(50) Name of vendor. tblVendor VendorId: INTEGER Vendor identifier. Vendor: VARCHAR2(50) Name of vendor. PhoneNumber: VARCHAR2(15) Phone number of vendor. FaxNumber: VARCHAR2(15) Fax Number of vendor. Address: VARCHAR2(50) Address of vendor. City: VARCHAR2(50) City of vendor. State: VARCHAR2(50) State of vendor. Zip: VARCHAR2(50) Zip code of vendor. tblPrimerOrderDesignMap PrimerId: INTEGER Reference to primer table. OrderId: INTEGER Reference to order table. tblWafer WaferId: INTEGER Wafer identifier. LotId: INTEGER Lot to which wafer belongs. Code: VARCHAR2(8) Code for wafer. SynthesisDate_delete: DATE Synthesis date for wafer. Released: DATE Date wafer available. Done: SMALLINT Whether wafer production is complete. ExpirationDate: DATE Expiration date of wafer. ExpectedLife: CHAR(18) Expected useful life of wafer. tblLot LotId: INTEGER Lot identifier. WaferDesignId: INTEGER Identifier for wafer design. LotNumber: VARCHAR2(12) Lot number. WaferPN: VARCHAR2(50) Part number for wafer. tblTiling Design TilingDesignID: INTEGER Tiling design identifier. ChipDesignSequenceMapID: NUMBER Reference to chip design sequence map. TilingFormatID: INTEGER Reference to tiling format table. UnitNumber: INTEGER 1 for sense, 0 for antisense AtomOffset: INTEGER # to add to translate atom position in tiling to atom position in chip design tblTiling Format TilingFormatID: INTEGER Tiling format identifier Orientation: CHAR(18) Orientation for tiling. ProbeLength: SMALLINT Length of probes. SubstitutionPosition: SMALLINT Substitution position for mutation base in probes. tblAtomDesign AtomDesignId: NUMBER Atom design identifier. TilingDesignID: INTEGER Reference to tiling design table. Position: INTEGER Position of atom in sequence. tblProbeDesign ProbeDesignID: NUMBER Probe design identifier. ChipDesignId: INTEGER Reference to chip design. x: SMALLINT x position of probe. y: SMALLINT y position of probe. tblProbeDesignRole ProbeDesignID: NUMBER Reference to probe design table. AtomDesignID: NUMBER Reference to atom design table. Substitution: CHAR(18) Substitution position in probe design. Mismatches: NUMBER Whether probe is match or mismatch. tblProbeData ProbeDesignID: NUMBER Reference to probe design table. ScanExptID: INTEGER Reference to scan experiment table. Intensity: FLOAT Measured hybridization intensity for probe. NPixels; NUMBER Number of pixels used for intensity calculation. StDev: NUMBER Standard deviation for pixels. tblAnalysis AnalysisId: INTEGER Analysis identifier. AnalysisVersionID: INTEGER Reference to version of analysis. ProtocolID: INTEGER Reference to protocol table. DatePerformed: DATE Date analysis performed. NeedsUpdate: NUMBER Whether analysis is current. tblAnalysisDependency ParentAnalysisId: INTEGER Analysis providing input. SubAnalysisId: INTEGER Analysis receiving input. Role: VARCHAR2(20) Role of data provided by parent analysis. TblAnalysisInput AnalysisinputID: INTEGER Analysis input identifier. AnalysisId: INTEGER Analysis receiving input. Inputtype: VARCHAR2(20) Type of input. ObjectID: INTEGER Reference to input data. tblChipDesignSequenceMap ChipDesignSequenceMapID: NUMBER Chip design sequence map identifier. FragmentID: INTEGER Reference to fragment table. ChipDesignId: INTEGER Chip design identifier. AtomOffset: NUMBER # to add to translate atom position in tiling to atom position in chip design tblSequencePosition SequencePositionID: NUMBER Sequence position identifier. ChipDesignSequenceMapID: NUMBER Reference to chip design sequence map table. Position: NUMBER Position in fragment. GenomicSequencePositionID: INTEGER Reference to genomic sequence position table. RefBase: INTEGER Reference base. tblGenomicSequencePosition GenomicSequencePositionID: INTEGER Genomic sequence position identifier. tblScanExperimentSet ScanExperimentSetID: NUMBER Scan experiment set identifier. tbsScanExperimentUsed ScanExptID: INTEGER Reference to scan experiment table. ScanExperimentSetID: NUMBER Reference to scan experiment set table. tblTilingData TilingDataID: NUMBER Tiling data identifier. ScanExptID: INTEGER Reference to scan experiment table. TilingDesignID: INTEGER Reference to tiling design table. tblAtomData AtomDataID: INTEGER Atom data identifier. TilingDataID: NUMBER Reference to tiling data table. SubjectSequencePositionID: INTEGER Reference to subject sequence position table. tblSubjectSequencePosition SubjectSequencePositionID: INTEGER Subject sequence position identifier. SubjectID: INTEGER Reference to subject table. SequencePositionID: NUMBER Reference to sequence position table. tblPolymorphismAnalysis AnalysisId: INTEGER Reference to analysis table. tblPolyPositionResult AnalysisId: INTEGER Reference to analysis table. PolyPositionID: INTEGER Polymorphism position identifier. ScanExperimentSetID: NUMBER Reference to scan experiment set table. PolyPositiontypeID: INTEGER Refers to possibility of polymorphism at position, e.g., certain, likely, possible, mismatch (reference is wrong). WTBase: CHAR(18) Wild type base at position. MuBase: INTEGER Mutation base at position. tblUserPolyanalysis AnalysisId: INTEGER Reference to analysis table. tblUserPolyanalysisResult AnalysisId: INTEGER Reference to analysis table. SequencePositionID: NUMBER Reference to sequence position table. ScanExperimentSetID: NUMBER Reference to scan experiment set table. PolyPositionTypeID: INTEGER See polymorphism position result table. UserComment: VARCHAR2(256) User comment done polymorphism analysis. tblAtomanalysis AnalysisId: INTEGER Reference to analysis table. tblAtomResult AnalysisId: INTEGER Reference to analysis table. AtomDataID: INTEGER Reference to atom data table. PHat: FLOAT Relative concentration of mutant and wild type. PHatUpperbound: FLOAT Upperbound for relative concentration. PHatLowerbound: FLOAT Lowerbound for relative concentration. MaxIntensity: FLOAT Maximum measured intensity for atom. WTIntensity: FLOAT Measured wild type intensity. MutIntensity: FLOAT Measured mutation intensity. LocalWTCallRate: FLOAT rate at which atoms associated with surrounding sequence call reference base IntensityRatio: FLOAT Ratio of intensity of wild type probe over intensity of mutation probe. tblBaseCallAnalysis AnalysisId: INTEGER Reference to analysis table. tblBaseCallResult AnalysisId: INTEGER Reference to analysis table. SubjectSequencePositionID: INTEGER Reference to sequence position table. ScanExperimentSetID: NUMBER Reference to skin experiments set table. CalledBase: VARCHAR2(1) Base called for subject based on experiment set. SuggestCheck: NUMBER Used to indicate whether this sample should be used for resequencing tblClusteringAnalysis AnalysisId: INTEGER Reference to analysis table. tblClusteringResult AnalysisId: INTEGER Reference to analysis table. SequencePositionID: NUMBER Reference to sequence position table. ScanExperimentSetID: NUMBER Reference to scan experiment set table. ClusteringFactor: FLOAT Result of clustering analysis. tblNormalizationRegionAnalysis AnalysisId: INTEGER Reference to analysis table. tblNormalizationRegion NormalizationRegionID: INTEGER Normalization region identifier. AnalysisId: INTEGER Reference to analysis table. ChipDesignSequenceMapID: NUMBER Reference to chip design sequence map table. NumberScanExpt.Set Reference to scan experiment set table. RegionEnd: INTEGER Indication of end of the normalization region. RegionStart: INTEGER Indication of beginning of the normalization region. tblNormalizationAnalysis AnalysisId: INTEGER Reference to analysis table. tblNormalizationResult NormalizationResultID: INTEGER Normalization result identifier. AnalysisId: INTEGER Reference to analysis table. TilingDataID: INTEGER Reference to tiling data table. NormalizationRegionResultID: INTEGER Reference to normalization result. NormalizationValue: NUMBER Value used for normalization. DataOK: NUMBER Indication whether normalization result is usable. tblFootprintAnalysis AnalysisId: INTEGER Reference to analysis table. tblFootprint FootprintID: NUMBER Footprint identifier. AnalysisId: INTEGER Analysis identifier. ChipDesignSequenceMapID: NUMBER Reference to chip design sequence map table. ScanExperimentSetID: NUMBER Reference to scan experiment set table. FFStart: NUMBER Start of footprint and sequence. FPEnd: NUMBER End of footprint and sequence. tblTilingDataQualityAnalysis AnalysisId: INTEGER Reference to analysis table. tbltilingDataQualityResult TilingDataID: NUMBER Reference to tiling data table. AnalysisId: INTEGER Reference to analysis table. AvgWTIntensity: NUMBER Average wild type intensity. WTCallRate: NUMBER Fraction of atoms where brightest of probes is one with reference space. AcceptData: INTEGER Whether data is of acceptable quality. tblDifficult Regionanalysis AnalysisId: INTEGER Reference to analysis table. tblDifficultRegionResult ScanExptId: INTEGER Reference to scan experiment table. AnalysisId: INTEGER Reference to analysis table. ChipDesignSequenceMapID: NUMBER Reference to chip design sequence map table. RgnStart: NUMBER Beginning of difficult region in sequence. RgnEnd: NUMBER End of difficult region in sequence. Reason: INTEGER Code indicating reason for difficult region, e.g., two or more non-wild type bases and less than a probe length. q tblPolyPatentSeq PolyPatentSeqId: NUMBER Polymorphism sequence identifier. Polyscreen: VARCHAR2(50) reference to internal grouping of polymorphisms FragmentCode: VARCHAR2(50) Fragment sequence found in Position: LONG Position of polymorphism. RefAllel: CHAR(2) Wild type base at position. FreqP: FLOAT Frequency of wild type. AltAllele: CHAR(2) Mutation base at position. FreqQ: FLOAT Frequency of mutation base. Heterozygocity: FLOAT Heterozygocity value. SequenceTag: VARCHAR2(50) Sequence containing polymorphism including ambiguity code at polymorphism position. GeneName: VARCHAR2(50) Name of gene. ChromosomeNum: VARCHAR2(20) Chromosome number. ChromosomeLoc: VARCHAR2(20) Location of gene on chromosome. ForwardPrimer: VARCHAR2(50) Identifier for forward primer used to implement fragment. ReversePrimer: VARCHAR2(50) Identifier of primer used to amplify fragment. tblPatentApp PatentAppId: NUMBER Patent application identifier. GroupId: NUMBER Reference to employee group table. AttorneyId: NUMBER Reference to attorney table. DocketNum: VARCHAR2(30) Docket number for patent application. FilingDate: DATE Filing date for filing application. Classification: VARCHAR2(30) Patent office classification for patent application. SerialNumber: VARCHAR2(50) Serial number assigned by patent office. CountryCode: VARCHAR2(50) Country in which patent application was filed. InventionTitle: VARCHAR2(100) Title for patent application tblPolyPatentSeqMap PatentAppId: NUMBER Reference to patent application table. PolyPatentSeqId: NUMBER Reference to polymorphism patent sequence table. tblPriorApp PriorAppId: NUMBER Reference to related prior patent application in patent application table. AppId: NUMBER Reference to application to which prior application is related. tblAttorney AttorneyId: NUMBER Attorney identifier. LawFirmId: NUMBER Law firm where attorney works. FirstName: VARCHAR2(20) First name of attorney. MiddleName: VARCHAR2(5) Middle name of attorney. LastName: VARCHAR2(30) Last name of attorney. RegistrationNum: VARCHAR2(25) Patent office registration number of attorney. tblLawFirm LawFirmId: NUMBER Law firm identifier. Company: VARCHAR2(100) Name of law firm. Address: VARCHAR2(100) Address of law firm. City: VARCHAR2(30) City address of law firm. State: VARCHAR2(20) State address of law firm. ZipCode: VARCHAR2(15) Zip Code of law firm. Country: VARCHAR2(15) Country of law firm. Telephone: VARCHAR2(30) Telephone number of law firm. Fax: VARCHAR2(30) TELEX: VARCHAR2(20) Facsimile number of law firm. Telex number of law firm. tblEmployeeGroup GroupId: NUMBER Identifier for inventor group. GroupName: VARCHAR2(50) Name of inventor group. Comments: VARCHAR2(50) Comments. GroupList: VARCHAR2(255) Written out list of inventor names. tblEmployeeGrpMap EmployeeId: INTEGER Reference to employee table for inventor/employees. GroupId: NUMBER Reference to inventor group table. - It is understood that the examples and embodiments described herein are for illustrative purposes only and that various modifications or changes in light thereof will be suggested to persons skilled in the art and are to be included within the spirit and purview of this application and scope of the appended claims. For example, tables may be deleted, contents of multiple tables may be consolidated, or contents of one or more tables may be distributed among more tables than described herein to improve query speeds and/or to aid system maintenance. Also, the database architecture and data models described herein are not limited to biological applications but may be used in any application. All publications, patents, and patent applications cited herein are hereby incorporated by reference.
Claims (2)
1. A computer-readable storage medium having stored thereon:
an item table listing a plurality of item records identifying items;
an item attribute table listing a plurality of item attribute records identifying attributes of said items; and
wherein there is a many-to-many relationship between item records and item attribute records.
2-23. (canceled)
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US11/038,624 US20050164270A1 (en) | 1997-07-25 | 2005-01-18 | Methods and system for providing a polymorphism database |
Applications Claiming Priority (7)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US5384297P | 1997-07-25 | 1997-07-25 | |
US6919897P | 1997-12-11 | 1997-12-11 | |
US6943697P | 1997-12-11 | 1997-12-11 | |
US6984997P | 1997-12-17 | 1997-12-17 | |
US09/122,169 US6484183B1 (en) | 1997-07-25 | 1998-07-24 | Method and system for providing a polymorphism database |
US10/219,021 US20030074363A1 (en) | 1997-07-25 | 2002-08-14 | Method and system for providing a polymorphism database |
US11/038,624 US20050164270A1 (en) | 1997-07-25 | 2005-01-18 | Methods and system for providing a polymorphism database |
Related Parent Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US10/219,021 Continuation US20030074363A1 (en) | 1997-07-25 | 2002-08-14 | Method and system for providing a polymorphism database |
Publications (1)
Publication Number | Publication Date |
---|---|
US20050164270A1 true US20050164270A1 (en) | 2005-07-28 |
Family
ID=27368502
Family Applications (10)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US09/122,304 Expired - Lifetime US6188783B1 (en) | 1997-07-25 | 1998-07-24 | Method and system for providing a probe array chip design database |
US09/122,434 Expired - Lifetime US6308170B1 (en) | 1997-07-25 | 1998-07-24 | Gene expression and evaluation system |
US09/122,167 Expired - Lifetime US6229911B1 (en) | 1997-07-25 | 1998-07-24 | Method and apparatus for providing a bioinformatics database |
US09/122,169 Expired - Lifetime US6484183B1 (en) | 1997-07-25 | 1998-07-24 | Method and system for providing a polymorphism database |
US09/836,867 Expired - Lifetime US6567540B2 (en) | 1997-07-25 | 2001-04-16 | Method and apparatus for providing a bioinformatics database |
US09/940,285 Expired - Lifetime US6532462B2 (en) | 1997-07-25 | 2001-08-27 | Gene expression and evaluation system using a filter table with a gene expression database |
US10/219,021 Abandoned US20030074363A1 (en) | 1997-07-25 | 2002-08-14 | Method and system for providing a polymorphism database |
US10/374,170 Expired - Lifetime US6882742B2 (en) | 1997-07-25 | 2003-02-25 | Method and apparatus for providing a bioinformatics database |
US11/038,624 Abandoned US20050164270A1 (en) | 1997-07-25 | 2005-01-18 | Methods and system for providing a polymorphism database |
US11/080,216 Expired - Fee Related US7215804B2 (en) | 1997-07-25 | 2005-03-14 | Method and apparatus for providing a bioinformatics database |
Family Applications Before (8)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US09/122,304 Expired - Lifetime US6188783B1 (en) | 1997-07-25 | 1998-07-24 | Method and system for providing a probe array chip design database |
US09/122,434 Expired - Lifetime US6308170B1 (en) | 1997-07-25 | 1998-07-24 | Gene expression and evaluation system |
US09/122,167 Expired - Lifetime US6229911B1 (en) | 1997-07-25 | 1998-07-24 | Method and apparatus for providing a bioinformatics database |
US09/122,169 Expired - Lifetime US6484183B1 (en) | 1997-07-25 | 1998-07-24 | Method and system for providing a polymorphism database |
US09/836,867 Expired - Lifetime US6567540B2 (en) | 1997-07-25 | 2001-04-16 | Method and apparatus for providing a bioinformatics database |
US09/940,285 Expired - Lifetime US6532462B2 (en) | 1997-07-25 | 2001-08-27 | Gene expression and evaluation system using a filter table with a gene expression database |
US10/219,021 Abandoned US20030074363A1 (en) | 1997-07-25 | 2002-08-14 | Method and system for providing a polymorphism database |
US10/374,170 Expired - Lifetime US6882742B2 (en) | 1997-07-25 | 2003-02-25 | Method and apparatus for providing a bioinformatics database |
Family Applications After (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US11/080,216 Expired - Fee Related US7215804B2 (en) | 1997-07-25 | 2005-03-14 | Method and apparatus for providing a bioinformatics database |
Country Status (6)
Country | Link |
---|---|
US (10) | US6188783B1 (en) |
EP (4) | EP1009861A4 (en) |
JP (6) | JP2001515234A (en) |
AT (1) | ATE264523T1 (en) |
DE (1) | DE69823206T2 (en) |
WO (4) | WO1999005574A1 (en) |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20070128647A1 (en) * | 2005-12-07 | 2007-06-07 | Affymetrix, Inc. | Methods for high throughput genotyping |
US20080287308A1 (en) * | 2007-05-18 | 2008-11-20 | Affymetrix, Inc. | System, method, and computer software product for genotype determination using probe array data |
Families Citing this family (321)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CA1223831A (en) | 1982-06-23 | 1987-07-07 | Dean Engelhardt | Modified nucleotides, methods of preparing and utilizing and compositions containing the same |
US5989835A (en) | 1997-02-27 | 1999-11-23 | Cellomics, Inc. | System for cell-based screening |
DE69823206T2 (en) * | 1997-07-25 | 2004-08-19 | Affymetrix, Inc. (a Delaware Corp.), Santa Clara | METHOD FOR PRODUCING A BIO-INFORMATICS DATABASE |
US7068830B2 (en) * | 1997-07-25 | 2006-06-27 | Affymetrix, Inc. | Method and system for providing a probe array chip design database |
US6826296B2 (en) * | 1997-07-25 | 2004-11-30 | Affymetrix, Inc. | Method and system for providing a probe array chip design database |
US6420108B2 (en) * | 1998-02-09 | 2002-07-16 | Affymetrix, Inc. | Computer-aided display for comparative gene expression |
US6990221B2 (en) * | 1998-02-07 | 2006-01-24 | Biodiscovery, Inc. | Automated DNA array image segmentation and analysis |
US6349144B1 (en) * | 1998-02-07 | 2002-02-19 | Biodiscovery, Inc. | Automated DNA array segmentation and analysis |
AU771877B2 (en) * | 1998-03-26 | 2004-04-01 | Incyte Pharmaceuticals, Inc. | Computer system and methods for analyzing biomolecular sequences |
US6324479B1 (en) * | 1998-05-08 | 2001-11-27 | Rosetta Impharmatics, Inc. | Methods of determining protein activity levels using gene expression profiles |
US6606622B1 (en) * | 1998-07-13 | 2003-08-12 | James M. Sorace | Software method for the conversion, storage and querying of the data of cellular biological assays on the basis of experimental design |
US6185561B1 (en) * | 1998-09-17 | 2001-02-06 | Affymetrix, Inc. | Method and apparatus for providing and expression data mining database |
US20040199544A1 (en) * | 2000-11-02 | 2004-10-07 | Affymetrix, Inc. | Method and apparatus for providing an expression data mining database |
WO2000029984A2 (en) | 1998-11-13 | 2000-05-25 | Cellomics, Inc. | Methods and system for efficient collection and storage of experimental data |
US6453241B1 (en) * | 1998-12-23 | 2002-09-17 | Rosetta Inpharmatics, Inc. | Method and system for analyzing biological response signal data |
US6136541A (en) | 1999-02-22 | 2000-10-24 | Vialogy Corporation | Method and apparatus for analyzing hybridized biochip patterns using resonance interactions employing quantum expressor functions |
US6142681A (en) | 1999-02-22 | 2000-11-07 | Vialogy Corporation | Method and apparatus for interpreting hybridized bioelectronic DNA microarray patterns using self-scaling convergent reverberant dynamics |
US20040111219A1 (en) * | 1999-02-22 | 2004-06-10 | Sandeep Gulati | Active interferometric signal analysis in software |
US6245511B1 (en) * | 1999-02-22 | 2001-06-12 | Vialogy Corp | Method and apparatus for exponentially convergent therapy effectiveness monitoring using DNA microarray based viral load measurements |
US6507788B1 (en) * | 1999-02-25 | 2003-01-14 | Société de Conseils de Recherches et D'Applications Scientifiques (S.C.R.A.S.) | Rational selection of putative peptides from identified nucleotide, or peptide sequences, of unknown function |
US6215894B1 (en) * | 1999-02-26 | 2001-04-10 | General Scanning, Incorporated | Automatic imaging and analysis of microarray biochips |
JP2000258368A (en) * | 1999-03-12 | 2000-09-22 | Jeol Ltd | X-ray microanalyzer having sound monitor function |
EP1041514B1 (en) * | 1999-03-30 | 2006-03-01 | Fuji Photo Film Co., Ltd. | Method and apparatus for selectively displaying measurement result and corresponding images |
US6446072B1 (en) * | 1999-04-13 | 2002-09-03 | Michael D. Schulze | Method of obtaining an electronically-stored financial document |
US6876760B1 (en) | 2000-12-04 | 2005-04-05 | Cytokinetics, Inc. | Classifying cells based on information contained in cell images |
US20030228565A1 (en) * | 2000-04-26 | 2003-12-11 | Cytokinetics, Inc. | Method and apparatus for predictive cellular bioinformatics |
US6651008B1 (en) | 1999-05-14 | 2003-11-18 | Cytokinetics, Inc. | Database system including computer code for predictive cellular bioinformatics |
US6743576B1 (en) | 1999-05-14 | 2004-06-01 | Cytokinetics, Inc. | Database system for predictive cellular bioinformatics |
US7151847B2 (en) | 2001-02-20 | 2006-12-19 | Cytokinetics, Inc. | Image analysis of the golgi complex |
US6334099B1 (en) | 1999-05-25 | 2001-12-25 | Digital Gene Technologies, Inc. | Methods for normalization of experimental data |
JP3469504B2 (en) * | 1999-06-01 | 2003-11-25 | 日立ソフトウエアエンジニアリング株式会社 | Microarray chip and indexing method thereof |
US6716579B1 (en) | 1999-06-11 | 2004-04-06 | Narayan Baidya | Gene specific arrays, preparation and use |
EP1185701A1 (en) * | 1999-06-11 | 2002-03-13 | Clingenix, Inc. | Gene specific arrays and the use thereof |
US7058517B1 (en) | 1999-06-25 | 2006-06-06 | Genaissance Pharmaceuticals, Inc. | Methods for obtaining and using haplotype data |
US6931396B1 (en) | 1999-06-29 | 2005-08-16 | Gene Logic Inc. | Biological data processing |
US6631211B1 (en) * | 1999-07-08 | 2003-10-07 | Perkinelmer Las, Inc. | Interactive system for analyzing scatter plots |
AU6611900A (en) * | 1999-07-30 | 2001-03-13 | Agy Therapeutics, Inc. | Techniques for facilitating identification of candidate genes |
US7062076B1 (en) | 1999-08-27 | 2006-06-13 | Iris Biotechnologies, Inc. | Artificial intelligence system for genetic analysis |
CA2420717C (en) * | 1999-08-27 | 2010-07-27 | Iris Biotechnologies, Inc. | Artificial intelligence system for genetic analysis |
AU2246601A (en) | 1999-08-30 | 2001-04-10 | Illumina, Inc. | Methods for improving signal detection from an array |
US7099502B2 (en) * | 1999-10-12 | 2006-08-29 | Biodiscovery, Inc. | System and method for automatically processing microarrays |
KR20020064298A (en) | 1999-10-13 | 2002-08-07 | 시쿼넘, 인코포레이티드 | Methods for generating databases and databases for identifying polymorphic genetic markers |
WO2001031333A1 (en) * | 1999-10-26 | 2001-05-03 | Genometrix Genomics Incorporated | Process for requesting biological experiments and for the delivery of experimental information |
EP2210948A3 (en) | 1999-12-10 | 2010-10-06 | Life Technologies Corporation | Use of multiple recombination sites with unique specificity in recombinational cloning |
AU2001237965A1 (en) * | 2000-01-25 | 2001-08-07 | Affymetrix, Inc. | Method, system and computer software for providing a genomic web portal |
US7356416B2 (en) | 2000-01-25 | 2008-04-08 | Cellomics, Inc. | Method and system for automated inference creation of physico-chemical interaction knowledge from databases of co-occurrence data |
US20030097222A1 (en) * | 2000-01-25 | 2003-05-22 | Craford David M. | Method, system, and computer software for providing a genomic web portal |
US7955794B2 (en) * | 2000-09-21 | 2011-06-07 | Illumina, Inc. | Multiplex nucleic acid reactions |
US8076063B2 (en) | 2000-02-07 | 2011-12-13 | Illumina, Inc. | Multiplexed methylation detection methods |
US20050214825A1 (en) * | 2000-02-07 | 2005-09-29 | John Stuelpnagel | Multiplex sample analysis on universal arrays |
US7582420B2 (en) * | 2001-07-12 | 2009-09-01 | Illumina, Inc. | Multiplex nucleic acid reactions |
US6770441B2 (en) | 2000-02-10 | 2004-08-03 | Illumina, Inc. | Array compositions and methods of making same |
NZ521626A (en) | 2000-03-29 | 2005-09-30 | Cambia | Methods for genotyping by hybridization analysis |
DE10015816A1 (en) * | 2000-03-30 | 2001-10-18 | Infineon Technologies Ag | Biosensor chip |
EP1272224A4 (en) * | 2000-03-31 | 2004-09-29 | Gene Logic Inc | Gene expression profiles in esophageal tissue |
AU784944B2 (en) * | 2000-04-18 | 2006-08-03 | Combimatrix Corporation | Automated system and process for custom-designed biological array design and analysis |
US20030171876A1 (en) * | 2002-03-05 | 2003-09-11 | Victor Markowitz | System and method for managing gene expression data |
US7020561B1 (en) | 2000-05-23 | 2006-03-28 | Gene Logic, Inc. | Methods and systems for efficient comparison, identification, processing, and importing of gene expression data |
US6741986B2 (en) * | 2000-12-08 | 2004-05-25 | Ingenuity Systems, Inc. | Method and system for performing information extraction and quality control for a knowledgebase |
US7577683B2 (en) * | 2000-06-08 | 2009-08-18 | Ingenuity Systems, Inc. | Methods for the construction and maintenance of a knowledge representation system |
US6772160B2 (en) * | 2000-06-08 | 2004-08-03 | Ingenuity Systems, Inc. | Techniques for facilitating information acquisition and storage |
US6931326B1 (en) | 2000-06-26 | 2005-08-16 | Genaissance Pharmaceuticals, Inc. | Methods for obtaining and using haplotype data |
US20020152196A1 (en) * | 2000-07-07 | 2002-10-17 | Westbrook Carol A. | cDNA database and biochip for analysis of hematopoietic tissue |
JP3517644B2 (en) * | 2000-07-13 | 2004-04-12 | 孝 五條堀 | Method and system for displaying expression phenomenon of living organisms and program |
US20020059326A1 (en) * | 2000-07-25 | 2002-05-16 | Derek Bernhart | System, method, and computer program product for management of biological experiment information |
NL1016034C2 (en) | 2000-08-03 | 2002-02-08 | Tno | Method and system for identifying and quantifying chemical components of a mixture of materials to be investigated. |
US7198924B2 (en) | 2000-12-11 | 2007-04-03 | Invitrogen Corporation | Methods and compositions for synthesis of nucleic acid molecules using multiple recognition sites |
US6789040B2 (en) | 2000-08-22 | 2004-09-07 | Affymetrix, Inc. | System, method, and computer software product for specifying a scanning area of a substrate |
WO2002017190A1 (en) * | 2000-08-22 | 2002-02-28 | Varro Technologies, Inc. | Method and system for sharing biological information |
EP1573634A2 (en) | 2000-08-22 | 2005-09-14 | Affymetrix, Inc. | System method, and computer software product for controlling biological microarray scanner |
GB0021286D0 (en) * | 2000-08-30 | 2000-10-18 | Gemini Genomics Ab | Identification of drug metabolic capacity |
US6539102B1 (en) * | 2000-09-01 | 2003-03-25 | Large Scale Proteomics | Reference database |
US6813615B1 (en) | 2000-09-06 | 2004-11-02 | Cellomics, Inc. | Method and system for interpreting and validating experimental data with automated reasoning |
AU2002212968A1 (en) * | 2000-09-12 | 2002-03-26 | Viaken Systems, Inc. | Techniques for providing and obtaining research and development information technology on remote computing resources |
JP2004512514A (en) * | 2000-10-23 | 2004-04-22 | ダイアチップ・リミテッド | High precision intelligent biochip arrayer with re-spot function |
US7117095B2 (en) * | 2000-11-21 | 2006-10-03 | Affymetrix, Inc. | Methods for selecting nucleic acid probes |
US8255791B2 (en) | 2000-11-29 | 2012-08-28 | Dov Koren | Collaborative, flexible, interactive real-time displays |
US7218764B2 (en) | 2000-12-04 | 2007-05-15 | Cytokinetics, Inc. | Ploidy classification method |
US6706867B1 (en) * | 2000-12-19 | 2004-03-16 | The United States Of America As Represented By The Department Of Health And Human Services | DNA array sequence selection |
US20020143768A1 (en) * | 2000-12-21 | 2002-10-03 | Berno Anthony Berno | Probe array data storage and retrieval |
AU2002237879A1 (en) * | 2001-01-23 | 2002-08-06 | Gene Logic, Inc. | A method and system for predicting the biological activity, including toxicology and toxicity, of substances |
US20020183936A1 (en) * | 2001-01-24 | 2002-12-05 | Affymetrix, Inc. | Method, system, and computer software for providing a genomic web portal |
US20070015148A1 (en) * | 2001-01-25 | 2007-01-18 | Orr Michael S | Gene expression profiles in breast tissue |
US20030017455A1 (en) * | 2001-01-29 | 2003-01-23 | Webb Peter G. | Chemical array fabrication with identity map |
US6949638B2 (en) * | 2001-01-29 | 2005-09-27 | Affymetrix, Inc. | Photolithographic method and system for efficient mask usage in manufacturing DNA arrays |
US7315784B2 (en) | 2001-02-15 | 2008-01-01 | Siemens Aktiengesellschaft | Network for evaluating data obtained in a biochip measurement device |
US6956961B2 (en) | 2001-02-20 | 2005-10-18 | Cytokinetics, Inc. | Extracting shape information contained in cell images |
US7016787B2 (en) | 2001-02-20 | 2006-03-21 | Cytokinetics, Inc. | Characterizing biological stimuli by response curves |
JP3867046B2 (en) * | 2001-02-23 | 2007-01-10 | 株式会社日立製作所 | Analysis system |
US7110885B2 (en) | 2001-03-08 | 2006-09-19 | Dnaprint Genomics, Inc. | Efficient methods and apparatus for high-throughput processing of gene sequence data |
US6804679B2 (en) * | 2001-03-12 | 2004-10-12 | Affymetrix, Inc. | System, method, and user interfaces for managing genomic data |
US20020168651A1 (en) * | 2001-03-12 | 2002-11-14 | Affymetrix, Inc. | Method and computer software product for determining orientation of sequence clusters |
JP2002269114A (en) * | 2001-03-14 | 2002-09-20 | Kousaku Ookubo | Knowledge database, and method for constructing knowledge database |
WO2002073504A1 (en) * | 2001-03-14 | 2002-09-19 | Gene Logic, Inc. | A system and method for retrieving and using gene expression data from multiple sources |
US20040033502A1 (en) * | 2001-03-28 | 2004-02-19 | Amanda Williams | Gene expression profiles in esophageal tissue |
JP2002297617A (en) * | 2001-03-29 | 2002-10-11 | Hitachi Software Eng Co Ltd | Method for displaying correlation between biopolymer and probe |
US7251568B2 (en) | 2001-04-18 | 2007-07-31 | Wyeth | Methods and compositions for regulating bone and cartilage formation |
WO2002085285A2 (en) * | 2001-04-18 | 2002-10-31 | Wyeth | Methods and reagents for regulating bone and cartilage formation |
US7155453B2 (en) * | 2002-05-22 | 2006-12-26 | Agilent Technologies, Inc. | Biotechnology information naming system |
US20070015146A1 (en) * | 2001-05-22 | 2007-01-18 | Gene Logic, Inc. | Molecular nephrotoxicology modeling |
WO2002095000A2 (en) * | 2001-05-22 | 2002-11-28 | Gene Logic, Inc. | Molecular toxicology modeling |
US20030009294A1 (en) * | 2001-06-07 | 2003-01-09 | Jill Cheng | Integrated system for gene expression analysis |
WO2002103030A2 (en) * | 2001-06-14 | 2002-12-27 | Rigel Pharmaceuticals, Inc. | Multidimensional biodata integration and relationship inference |
US20040215651A1 (en) * | 2001-06-22 | 2004-10-28 | Markowitz Victor M. | Platform for management and mining of genomic data |
KR100794698B1 (en) * | 2001-06-28 | 2008-01-14 | (주)바이오니아 | Quality control method for biological chip |
AU2002320316A1 (en) * | 2001-07-06 | 2003-01-21 | Lipomics Technologies, Inc. | Generating, viewing, interpreting, and utilizing a quantitative database of metabolites |
US7447594B2 (en) * | 2001-07-10 | 2008-11-04 | Ocimum Biosolutions, Inc. | Molecular cardiotoxicology modeling |
JP2005517400A (en) * | 2001-07-10 | 2005-06-16 | ジーン ロジック インコーポレイテッド | Cardiotoxin molecular toxicity modeling |
CN1537229A (en) * | 2001-07-31 | 2004-10-13 | ���ְ�˹��ʽ���� | Gene inspection apparatus and target nucleic acid extraction method using the same |
US7251642B1 (en) | 2001-08-06 | 2007-07-31 | Gene Logic Inc. | Analysis engine and work space manager for use with gene expression data |
JP3977038B2 (en) * | 2001-08-27 | 2007-09-19 | 株式会社半導体エネルギー研究所 | Laser irradiation apparatus and laser irradiation method |
US20030096248A1 (en) * | 2001-09-04 | 2003-05-22 | Vitivity, Inc. | Diagnosis and treatment of vascular disease |
CA2459508A1 (en) * | 2001-09-24 | 2003-04-03 | Lipomics Technologies, Inc. | Methods of using quantitative lipid metabolome data |
JP2003099624A (en) * | 2001-09-25 | 2003-04-04 | Toyo Kohan Co Ltd | Dna providing system |
AU2002334769A1 (en) * | 2001-10-12 | 2003-04-28 | Duke University | Image analysis of high-density synthetic dna microarrays |
US6993173B2 (en) * | 2001-10-12 | 2006-01-31 | Duke University | Methods for estimating probe cell locations in high-density synthetic DNA microarrays |
US20060141493A1 (en) * | 2001-11-09 | 2006-06-29 | Duke University Office Of Science And Technology | Atherosclerotic phenotype determinative genes and methods for using the same |
US20040255136A1 (en) * | 2001-11-12 | 2004-12-16 | Alexey Borisovich Fadyushin | Method and device for protecting information against unauthorised use |
KR100474840B1 (en) * | 2001-11-15 | 2005-03-08 | 삼성전자주식회사 | Method and system with directory for providing a genotyping microarray probe design |
US20030157700A1 (en) * | 2001-12-19 | 2003-08-21 | Affymetrix, Inc. | Apparatus and methods for constructing array plates |
US20030176929A1 (en) * | 2002-01-28 | 2003-09-18 | Steve Gardner | User interface for a bioinformatics system |
US7225183B2 (en) * | 2002-01-28 | 2007-05-29 | Ipxl, Inc. | Ontology-based information management system and method |
US9418204B2 (en) * | 2002-01-28 | 2016-08-16 | Samsung Electronics Co., Ltd | Bioinformatics system architecture with data and process integration |
US8793073B2 (en) | 2002-02-04 | 2014-07-29 | Ingenuity Systems, Inc. | Drug discovery methods |
JP4594622B2 (en) * | 2002-02-04 | 2010-12-08 | インジェヌイティ システムズ インコーポレイテッド | Drug discovery method |
US20030162183A1 (en) * | 2002-02-27 | 2003-08-28 | Robert Kincaid | Array design system and method |
WO2003082078A2 (en) * | 2002-03-28 | 2003-10-09 | Medical College Of Ohio | Method and compositions for the diagnosis and treatment of non-small cell lung cancer using gene expression profiles |
AU2002364707A1 (en) * | 2002-04-23 | 2003-11-10 | Duke University | Atherosclerotic phenotype determinative genes and methods for using the same |
DE60323625D1 (en) * | 2002-05-03 | 2008-10-30 | Vialogy Llc | METHOD FOR CHARACTERIZING THE OUTPUT SIGNALS OF A MICROARRAY |
US20030220844A1 (en) * | 2002-05-24 | 2003-11-27 | Marnellos Georgios E. | Method and system for purchasing genetic data |
US6763308B2 (en) | 2002-05-28 | 2004-07-13 | Sas Institute Inc. | Statistical outlier detection for gene expression microarray data |
US20030229848A1 (en) * | 2002-06-05 | 2003-12-11 | Udo Arend | Table filtering in a computer user interface |
US7504215B2 (en) | 2002-07-12 | 2009-03-17 | Affymetrix, Inc. | Nucleic acid labeling methods |
US20050112689A1 (en) * | 2003-04-04 | 2005-05-26 | Robert Kincaid | Systems and methods for statistically analyzing apparent CGH data anomalies and plotting same |
US20050216459A1 (en) * | 2002-08-08 | 2005-09-29 | Aditya Vailaya | Methods and systems, for ontological integration of disparate biological data |
US7941542B2 (en) * | 2002-09-06 | 2011-05-10 | Oracle International Corporation | Methods and apparatus for maintaining application execution over an intermittent network connection |
US7512496B2 (en) * | 2002-09-25 | 2009-03-31 | Soheil Shams | Apparatus, method, and computer program product for determining confidence measures and combined confidence measures for assessing the quality of microarrays |
AU2003282885A1 (en) * | 2002-09-30 | 2004-04-23 | Nimblegen Systems, Inc. | Parallel loading of arrays |
CA2500783C (en) * | 2002-10-01 | 2012-07-17 | Nimblegen Systems, Inc. | Microarrays having multiple oligonucleotides in single array features |
US20040259105A1 (en) * | 2002-10-03 | 2004-12-23 | Jian-Bing Fan | Multiplex nucleic acid analysis using archived or fixed samples |
US9453251B2 (en) | 2002-10-08 | 2016-09-27 | Pfenex Inc. | Expression of mammalian proteins in Pseudomonas fluorescens |
EP1562570A4 (en) * | 2002-11-06 | 2007-09-05 | Sinai School Medicine | Treatment of amyotrophic lateral sclerosis with nimesulide |
EP2112229A3 (en) | 2002-11-25 | 2009-12-02 | Sequenom, Inc. | Methods for identifying risk of breast cancer and treatments thereof |
WO2004050840A2 (en) * | 2002-11-27 | 2004-06-17 | The Government Of The United States As Represented By The Secretary Of The Department Of Health And Human Services, Centers For Disease Control And Prevention | Integration of gene expression data and non-gene data |
JP2004191160A (en) * | 2002-12-11 | 2004-07-08 | Yokogawa Electric Corp | Biochip measuring method and device |
KR100506089B1 (en) * | 2003-02-05 | 2005-08-05 | 삼성전자주식회사 | System for designing probe array using heterogeneneous genomic information and method of the same |
US7750908B2 (en) * | 2003-04-04 | 2010-07-06 | Agilent Technologies, Inc. | Focus plus context viewing and manipulation of large collections of graphs |
EP1613734A4 (en) * | 2003-04-04 | 2007-04-18 | Agilent Technologies Inc | Visualizing expression data on chromosomal graphic schemes |
US7825929B2 (en) * | 2003-04-04 | 2010-11-02 | Agilent Technologies, Inc. | Systems, tools and methods for focus and context viewing of large collections of graphs |
CA2523875A1 (en) * | 2003-04-28 | 2004-11-11 | Public Health Agency Of Canada | Sars virus nucleotide and amino acid sequences and uses thereof |
US20040249791A1 (en) * | 2003-06-03 | 2004-12-09 | Waters Michael D. | Method and system for developing and querying a sequence driven contextual knowledge base |
CA3084542A1 (en) | 2003-06-10 | 2005-01-06 | The Trustees Of Boston University | Gene expression analysis of airway epithelial cells for diagnosing lung cancer |
US20050064462A1 (en) * | 2003-06-17 | 2005-03-24 | Bernd Stein | Methods, compositions, and kits for predicting the effect of compounds on hot flash symptoms |
US20050014217A1 (en) | 2003-07-18 | 2005-01-20 | Cytokinetics, Inc. | Predicting hepatotoxicity using cell based assays |
US7235353B2 (en) | 2003-07-18 | 2007-06-26 | Cytokinetics, Inc. | Predicting hepatotoxicity using cell based assays |
US7246012B2 (en) | 2003-07-18 | 2007-07-17 | Cytokinetics, Inc. | Characterizing biological stimuli by response curves |
US20050026154A1 (en) * | 2003-07-31 | 2005-02-03 | Laurakay Bruhn | Masking chemical arrays |
US20050026306A1 (en) * | 2003-07-31 | 2005-02-03 | Robert Kincaid | Method and system for generating virtual-microarrays |
US7353116B2 (en) * | 2003-07-31 | 2008-04-01 | Agilent Technologies, Inc. | Chemical array with test dependent signal reading or processing |
US7475087B1 (en) | 2003-08-29 | 2009-01-06 | The United States Of America As Represented By The Secretary Of Agriculture | Computer display tool for visualizing relationships between and among data |
US20050048506A1 (en) * | 2003-09-03 | 2005-03-03 | Fredrick Joseph P. | Methods for encoding non-biological information on microarrays |
US20050049796A1 (en) * | 2003-09-03 | 2005-03-03 | Webb Peter G. | Methods for encoding non-biological information on microarrays |
WO2005024068A2 (en) | 2003-09-05 | 2005-03-17 | Sequenom, Inc. | Allele-specific sequence variation analysis |
EP2287341B1 (en) | 2003-12-01 | 2013-02-13 | Life Technologies Corporation | Nucleic acid molecules containing recombination sites and methods of using the same |
US20050191682A1 (en) | 2004-02-17 | 2005-09-01 | Affymetrix, Inc. | Methods for fragmenting DNA |
US7660709B2 (en) * | 2004-03-18 | 2010-02-09 | Van Andel Research Institute | Bioinformatics research and analysis system and methods associated therewith |
CA2561381C (en) | 2004-03-26 | 2015-05-12 | Sequenom, Inc. | Base specific cleavage of methylation-specific amplification products in combination with mass analysis |
KR100632973B1 (en) * | 2004-04-29 | 2006-10-12 | 주식회사 메딘텔 | Circular matching system and method for circular matching |
US20060003335A1 (en) * | 2004-06-30 | 2006-01-05 | Crispino John D | Methods for diagnosing acute megakaryoblastic leukemia |
US7323318B2 (en) | 2004-07-15 | 2008-01-29 | Cytokinetics, Inc. | Assay for distinguishing live and dead cells |
EP1773860A4 (en) * | 2004-07-22 | 2009-05-06 | Sequenom Inc | Methods for identifying risk of type ii diabetes and treatments thereof |
US8603824B2 (en) | 2004-07-26 | 2013-12-10 | Pfenex, Inc. | Process for improved protein expression by strain engineering |
US8484000B2 (en) * | 2004-09-02 | 2013-07-09 | Vialogy Llc | Detecting events of interest using quantum resonance interferometry |
US20060073506A1 (en) | 2004-09-17 | 2006-04-06 | Affymetrix, Inc. | Methods for identifying biological samples |
US20060073511A1 (en) | 2004-10-05 | 2006-04-06 | Affymetrix, Inc. | Methods for amplifying and analyzing nucleic acids |
US20060083609A1 (en) * | 2004-10-14 | 2006-04-20 | Augspurger Murray D | Fluid cooled marine turbine housing |
CA2524964A1 (en) | 2004-10-29 | 2006-04-29 | Affymetrix, Inc. | Automated method of manufacturing polymer arrays |
US7682782B2 (en) | 2004-10-29 | 2010-03-23 | Affymetrix, Inc. | System, method, and product for multiple wavelength detection using single source excitation |
US20090068650A1 (en) * | 2005-02-11 | 2009-03-12 | Southern Illinois University | Metabolic Primers for the Detection of (Per) Chlorate-Reducing Bacteria and Methods of Use Thereof |
US20060211004A1 (en) | 2005-02-15 | 2006-09-21 | Ilsley Diane D | Methods and compositions for determining non-specific cytotoxicity of a transfection agent |
WO2006089046A2 (en) | 2005-02-18 | 2006-08-24 | Monogram Biosciences, Inc. | Methods and compositions for determining anti-hiv drug susceptibility and replication capacity of hiv |
WO2006089268A2 (en) * | 2005-02-18 | 2006-08-24 | The University Of North Carolina At Chapel Hill | Gene and cognate protein profiles and methods to determine connective tissue markers in normal and pathologic conditions |
WO2006089045A2 (en) | 2005-02-18 | 2006-08-24 | Monogram Biosciences, Inc. | Methods and compositions for determining hypersusceptibility of hiv-1 to non-nucleoside reverse transcriptase inhibitors |
US20070118295A1 (en) * | 2005-03-02 | 2007-05-24 | Al-Murrani Samer Waleed Khedhe | Methods and Systems for Designing Animal Food Compositions |
WO2007086890A2 (en) * | 2005-03-10 | 2007-08-02 | Genemark Inc. | Method, apparatus, and system for authentication using labels containing nucleotide seouences |
WO2006099421A2 (en) | 2005-03-14 | 2006-09-21 | The Board Of Trustees Of The Leland Stanford Junior University | Methods and compositions for evaluating graft survival in a solid organ transplant recipient |
EP3770278A1 (en) | 2005-04-14 | 2021-01-27 | The Trustees of Boston University | Diagnostic for lung disorders using class prediction |
WO2006116455A2 (en) | 2005-04-26 | 2006-11-02 | Applera Corporation | System for genetic surveillance and analysis |
US20090087841A1 (en) * | 2005-05-27 | 2009-04-02 | Monogram Biosciences, Inc. | Methods and compositions for determining resistance of hiv-1 to protease inhibitors |
US8071284B2 (en) * | 2005-06-06 | 2011-12-06 | Monogram Biosciences, Inc. | Methods and compositions for determining altered susceptibility of HIV-1 to anti-HIV drugs |
WO2006133266A2 (en) | 2005-06-06 | 2006-12-14 | Monogram Biosciences, Inc. | Methods for determining resistance or susceptibility to hiv entry inhibitors |
US8159959B2 (en) * | 2005-11-07 | 2012-04-17 | Vudu, Inc. | Graphic user interface for playing video data |
EP1969506A1 (en) * | 2005-12-13 | 2008-09-17 | Erasmus University Medical Center Rotterdam | Genetic brain tumor markers |
US7646450B2 (en) * | 2005-12-29 | 2010-01-12 | Lg Display Co., Ltd. | Light emitting diode array, method of manufacturing the same, backlight assembly having the same, and LCD having the same |
US20070198729A1 (en) * | 2006-02-07 | 2007-08-23 | Yechuri Sitaramarao S | SQL network gadget |
EP2605018A1 (en) | 2006-03-09 | 2013-06-19 | The Trustees of the Boston University | Diagnostic and prognostic methods for lung disorders using gene expression profiles from nose epithelial cells |
US20100285973A1 (en) * | 2006-05-30 | 2010-11-11 | Synergenz Bioscience Limited of Sea Meadow House | Methods and compositions for assessment of pulmonary function and disorders |
EP2029777B1 (en) | 2006-05-31 | 2017-03-08 | Sequenom, Inc. | Methods and compositions for the extraction of nucleic acid from a sample |
EP2035439A4 (en) | 2006-06-05 | 2010-01-13 | Cancer Care Ontario | Assessment of risk for colorectal cancer |
US20080033985A1 (en) * | 2006-06-09 | 2008-02-07 | Gulfstream Bioinformatics Corporation | Biomedical Information Modeling |
US7700756B2 (en) * | 2006-07-27 | 2010-04-20 | Southern Illinois University | Metabolic primers for the detection of perchlorate-reducing bacteria and methods of use thereof |
US20080033819A1 (en) * | 2006-07-28 | 2008-02-07 | Ingenuity Systems, Inc. | Genomics based targeted advertising |
JP5244103B2 (en) | 2006-08-09 | 2013-07-24 | ホームステッド クリニカル コーポレイション | Organ-specific protein and method of use thereof |
CA2666584A1 (en) * | 2006-10-17 | 2008-04-24 | Synergenz Bioscience Limited | Methods and compositions for assessment of pulmonary function and disorders |
US9845494B2 (en) | 2006-10-18 | 2017-12-19 | Affymetrix, Inc. | Enzymatic methods for genotyping on arrays |
CA2668235A1 (en) | 2006-11-02 | 2008-06-05 | Yale University | Assessment of oocyte competence |
NZ551157A (en) * | 2006-11-08 | 2008-06-30 | Rebecca Lee Roberts | Method of identifying individuals at risk of thiopurine drug resistance and intolerance - GMPS |
US8293684B2 (en) * | 2006-11-29 | 2012-10-23 | Exiqon | Locked nucleic acid reagents for labelling nucleic acids |
US7902345B2 (en) | 2006-12-05 | 2011-03-08 | Sequenom, Inc. | Detection and quantification of biomolecules using mass spectrometry |
CA2673092A1 (en) * | 2006-12-19 | 2008-06-26 | Synergenz Bioscience Limited | Methods and compositions for the assessment of cardiovascular function and disorders |
EP2993473A1 (en) | 2007-01-30 | 2016-03-09 | Pharmacyclics, Inc. | Methods for determining cancer resistance to histone deacetylase inhibitors |
WO2008098142A2 (en) | 2007-02-08 | 2008-08-14 | Sequenom, Inc. | Nucleic acid-based tests for rhd typing, gender determination and nucleic acid quantification |
US9581595B2 (en) | 2007-02-26 | 2017-02-28 | Laboratory Corporation Of America Holdings | Compositions and methods for determining whether a subject would benefit from co-receptor inhibitor therapy |
AU2008222563A1 (en) | 2007-03-05 | 2008-09-12 | Cancer Care Ontario | Assessment of risk for colorectal cancer |
US8652780B2 (en) | 2007-03-26 | 2014-02-18 | Sequenom, Inc. | Restriction endonuclease enhanced polymorphic sequence detection |
EP2615172A1 (en) | 2007-04-27 | 2013-07-17 | Pfenex Inc. | Method for rapidly screening microbial hosts to identify certain strains with improved yield and/or quality in the expression of heterologous proteins |
US9580719B2 (en) | 2007-04-27 | 2017-02-28 | Pfenex, Inc. | Method for rapidly screening microbial hosts to identify certain strains with improved yield and/or quality in the expression of heterologous proteins |
WO2009032781A2 (en) | 2007-08-29 | 2009-03-12 | Sequenom, Inc. | Methods and compositions for universal size-specific polymerase chain reaction |
US8765368B2 (en) * | 2007-09-17 | 2014-07-01 | The University Of Toledo | Cancer risk biomarker |
JP5592802B2 (en) | 2008-01-25 | 2014-09-17 | セラノスティクス ラボラトリー | Methods and compositions for assessing drug response |
AU2009223671B2 (en) | 2008-03-11 | 2014-11-27 | Sequenom, Inc. | Nucleic acid-based tests for prenatal gender determination |
EP2253713B1 (en) | 2008-03-11 | 2015-02-25 | National Cancer Center | Method for measuring chromosome, gene or specific nucleotide sequence copy numbers using snp array |
CA2718137A1 (en) | 2008-03-26 | 2009-10-01 | Sequenom, Inc. | Restriction endonuclease enhanced polymorphic sequence detection |
EP2297349A1 (en) * | 2008-06-04 | 2011-03-23 | The Arizona Board Of Regents On Behalf Of The University Of Arizona | Diffuse large b-cell lymphoma markers and uses therefor |
EP2324129A4 (en) | 2008-08-18 | 2012-06-20 | Univ Leland Stanford Junior | Methods and compositions for determining a graft tolerant phenotype in a subject |
US8476013B2 (en) * | 2008-09-16 | 2013-07-02 | Sequenom, Inc. | Processes and compositions for methylation-based acid enrichment of fetal nucleic acid from a maternal sample useful for non-invasive prenatal diagnoses |
US8962247B2 (en) | 2008-09-16 | 2015-02-24 | Sequenom, Inc. | Processes and compositions for methylation-based enrichment of fetal nucleic acid from a maternal sample useful for non invasive prenatal diagnoses |
WO2010054189A1 (en) | 2008-11-06 | 2010-05-14 | University Of Miami | Role of soluble upar in the pathogenesis of proteinuric kidney disease |
US8039794B2 (en) | 2008-12-16 | 2011-10-18 | Quest Diagnostics Investments Incorporated | Mass spectrometry assay for thiopurine-S-methyl transferase activity and products generated thereby |
KR101025848B1 (en) * | 2008-12-30 | 2011-03-30 | 삼성전자주식회사 | The method and apparatus for integrating and managing personal genome |
WO2010080933A1 (en) | 2009-01-07 | 2010-07-15 | Myriad Genetics, Inc | Cancer biomarkers |
EP3020830A1 (en) * | 2009-01-20 | 2016-05-18 | The Board Of Trustees Of The Leland Stanford Junior University | Single cell gene expression for diagnosis, prognosis and identification of drug targets |
JP2012517238A (en) | 2009-02-11 | 2012-08-02 | カリス エムピーアイ インコーポレイテッド | Molecular profiling of tumors |
US8832581B2 (en) * | 2009-03-05 | 2014-09-09 | Ming Zhang | Gene expression browser for web-based search and visualization of characteristics of gene expression |
EP2408936A4 (en) * | 2009-03-18 | 2013-01-30 | Sequenom Inc | Use of thermostable endonucleases for generating reporter molecules |
EP3211095B1 (en) | 2009-04-03 | 2019-01-02 | Sequenom, Inc. | Nucleic acid preparation compositions and methods |
WO2011056688A2 (en) | 2009-10-27 | 2011-05-12 | Caris Life Sciences, Inc. | Molecular profiling for personalized medicine |
US20110201008A1 (en) * | 2009-12-01 | 2011-08-18 | University Of Miami | Assays, methods and kits for measuring response to therapy and predicting clinical outcome in patients with b-cell lymphoma |
US9290813B2 (en) | 2009-12-02 | 2016-03-22 | The Board Of Trustees Of The Leland Stanford Junior University | Biomarkers for determining an allograft tolerant phenotype |
US8501122B2 (en) | 2009-12-08 | 2013-08-06 | Affymetrix, Inc. | Manufacturing and processing polymer arrays |
US8835358B2 (en) | 2009-12-15 | 2014-09-16 | Cellular Research, Inc. | Digital counting of individual molecules by stochastic attachment of diverse labels |
ES2577017T3 (en) | 2009-12-22 | 2016-07-12 | Sequenom, Inc. | Procedures and kits to identify aneuploidy |
US9798855B2 (en) | 2010-01-07 | 2017-10-24 | Affymetrix, Inc. | Differential filtering of genetic data |
US9216189B2 (en) | 2010-01-25 | 2015-12-22 | Icahn School Of Medicine At Mount Sinai | Antibodies which bind type I cannabinoid receptor/angiotensis II receptor heteromers |
CA2794255C (en) | 2010-03-25 | 2020-01-14 | Minnie M. Sarwal | Protein and gene biomarkers for rejection of organ transplants |
WO2011139714A2 (en) | 2010-04-26 | 2011-11-10 | Atyr Pharma, Inc. | Innovative discovery of therapeutic, diagnostic, and antibody compositions related to protein fragments of cysteinyl-trna synthetase |
CN103096911B (en) | 2010-04-27 | 2018-05-29 | Atyr 医药公司 | Treatment relevant with the protein fragments of Isoleucyl-tRNA synthetase, diagnosis and the innovation of antibody compositions are found |
WO2011139853A2 (en) | 2010-04-28 | 2011-11-10 | Atyr Pharma, Inc. | Innovative discovery of therapeutic, diagnostic, and antibody compositions related to protein fragments of alanyl trna synthetases |
CN103097523B (en) | 2010-04-29 | 2016-09-28 | Atyr医药公司 | The innovation for the treatment of, diagnosis and the antibody compositions relevant to the protein fragments of Asparaginyl-tRNA synthetase finds |
AU2011248457B2 (en) | 2010-04-29 | 2017-02-16 | Pangu Biopharma Limited | Innovative discovery of therapeutic, diagnostic, and antibody compositions related to protein fragments of valyl tRNA synthetases |
WO2011150279A2 (en) | 2010-05-27 | 2011-12-01 | Atyr Pharma, Inc. | Innovative discovery of therapeutic, diagnostic, and antibody compositions related to protein fragments of glutaminyl-trna synthetases |
CN105820252B (en) | 2010-05-03 | 2020-07-21 | Atyr 医药公司 | Innovative discovery of therapeutic, diagnostic, and antibody compositions related to protein fragments of phenylalanyl- α -tRNA synthetases |
US8981045B2 (en) | 2010-05-03 | 2015-03-17 | Atyr Pharma, Inc. | Innovative discovery of therapeutic, diagnostic, and antibody compositions related to protein fragments of methionyl-tRNA synthetases |
US8961961B2 (en) | 2010-05-03 | 2015-02-24 | a Tyr Pharma, Inc. | Innovative discovery of therapeutic, diagnostic, and antibody compositions related protein fragments of arginyl-tRNA synthetases |
CA2798139C (en) | 2010-05-04 | 2019-09-24 | Atyr Pharma, Inc. | Innovative discovery of therapeutic, diagnostic, and antibody compositions related to protein fragments of p38 multi-trna synthetase complex |
CN103200953B (en) | 2010-05-14 | 2017-02-15 | Atyr 医药公司 | Innovative discovery of therapeutic, diagnostic, and antibody compositions related to protein fragments of phenylalanyl-beta-trna synthetases |
EP2575857B1 (en) | 2010-06-01 | 2018-01-24 | aTyr Pharma, Inc. | Innovative discovery of therapeutic, diagnostic, and antibody compositions related to protein fragments of lysyl-trna synthetases |
CA2804391A1 (en) | 2010-07-07 | 2012-01-12 | Myriad Genetics, Inc. | Gene signatures for cancer prognosis |
AU2011289831C1 (en) | 2010-07-12 | 2017-06-15 | Pangu Biopharma Limited | Innovative discovery of therapeutic, diagnostic, and antibody compositions related to protein fragments of glycyl-tRNA synthetases |
CN103108650A (en) | 2010-08-25 | 2013-05-15 | Atyr医药公司 | Innovative discovery of therapeutic, diagnostic, and antibody compositions related to protein fragments of tyrosyl-trna synthetases |
US20120075325A1 (en) * | 2010-09-09 | 2012-03-29 | Abbott Laboratories | Systems and methods for displaying molecular probes and chromosomes |
KR20130115250A (en) | 2010-09-15 | 2013-10-21 | 알막 다이아그노스틱스 리미티드 | Molecular diagnostic test for cancer |
AU2012249531B2 (en) | 2011-04-29 | 2017-06-29 | Sequenom, Inc. | Quantification of a minority nucleic acid species |
EP3418397B1 (en) | 2012-01-24 | 2020-10-07 | CD Diagnostics, Inc. | System for detecting infection in synovial fluid |
EP3311847A1 (en) | 2012-02-16 | 2018-04-25 | Atyr Pharma, Inc. | Histidyl-trna synthetases for treating autoimmune and inflammatory diseases |
CA2865575C (en) | 2012-02-27 | 2024-01-16 | Cellular Research, Inc. | Compositions and kits for molecular counting |
US11177020B2 (en) | 2012-02-27 | 2021-11-16 | The University Of North Carolina At Chapel Hill | Methods and uses for molecular tags |
EP2820129A1 (en) | 2012-03-02 | 2015-01-07 | Sequenom, Inc. | Methods and processes for non-invasive assessment of genetic variations |
US9920361B2 (en) | 2012-05-21 | 2018-03-20 | Sequenom, Inc. | Methods and compositions for analyzing nucleic acid |
CA2878979C (en) | 2012-07-13 | 2021-09-14 | Sequenom, Inc. | Processes and compositions for methylation-based enrichment of fetal nucleic acid from a maternal sample useful for non-invasive prenatal diagnoses |
US8766754B2 (en) | 2012-07-18 | 2014-07-01 | The Regents Of The University Of California | Concave nanomagnets with widely tunable anisotropy |
WO2014078700A1 (en) | 2012-11-16 | 2014-05-22 | Myriad Genetics, Inc. | Gene signatures for cancer prognosis |
MX367366B (en) | 2012-11-27 | 2019-08-16 | Univ Pontificia Catolica Chile | Compositions and methods for diagnosing thyroid tumors. |
US9896728B2 (en) | 2013-01-29 | 2018-02-20 | Arcticrx Ltd. | Method for determining a therapeutic approach for the treatment of age-related macular degeneration (AMD) |
US11060145B2 (en) | 2013-03-13 | 2021-07-13 | Sequenom, Inc. | Methods and compositions for identifying presence or absence of hypermethylation or hypomethylation locus |
US10535420B2 (en) | 2013-03-15 | 2020-01-14 | Affymetrix, Inc. | Systems and methods for probe design to detect the presence of simple and complex indels |
EP4043580A1 (en) | 2013-03-15 | 2022-08-17 | Myriad myPath, LLC | Genes and gene signatures for diagnosis and treatment of melanoma |
KR101520615B1 (en) | 2013-03-20 | 2015-05-18 | 서울대학교산학협력단 | Markers for diagnosis of liver cancer |
US10390724B2 (en) | 2013-06-26 | 2019-08-27 | The Penn State Research Foundation | Three-dimensional bio-medical probe sensing and contacting structures with addressibility and tunability |
EA201690213A1 (en) | 2013-08-12 | 2016-07-29 | Дженентек, Инк. | COMPOSITIONS AND METHOD FOR TREATMENT OF CONNECTED STATES |
KR101527283B1 (en) | 2013-08-13 | 2015-06-10 | 서울대학교산학협력단 | Method for screening cancer marker based on de-glycosylation of glycoproteins and marker for HCC |
ES2873248T3 (en) | 2014-02-08 | 2021-11-03 | Hoffmann La Roche | Methods to treat Alzheimer's disease |
EP3117011B1 (en) | 2014-03-13 | 2020-05-06 | Sequenom, Inc. | Methods and processes for non-invasive assessment of genetic variations |
MX2016013877A (en) | 2014-04-22 | 2017-03-09 | Envirologix Inc | Compositions and methods for enhancing and/or predicting dna amplification. |
CA2947624A1 (en) | 2014-05-13 | 2015-11-19 | Myriad Genetics, Inc. | Gene signatures for cancer prognosis |
ES2946681T3 (en) | 2014-07-02 | 2023-07-24 | Myriad Mypath Llc | Genes and gene signatures for the diagnosis and treatment of melanoma |
WO2016061252A1 (en) | 2014-10-14 | 2016-04-21 | The University Of North Carolina At Chapel Hill | Methods and compositions for prognostic and/or diagnostic subtyping of pancreatic cancer |
EP4141128A1 (en) | 2014-10-20 | 2023-03-01 | Envirologix Inc. | Compositions and methods for detecting an rna virus |
JP7065609B6 (en) | 2014-10-24 | 2022-06-06 | コーニンクレッカ フィリップス エヌ ヴェ | Medical prognosis and prediction of therapeutic response using multiple cellular signaling pathway activities |
DK3210142T3 (en) | 2014-10-24 | 2020-11-16 | Koninklijke Philips Nv | ASSESSMENT OF TGF CELLULAR SIGNALING VEHICLE ACTIVITY USING MATHEMATICAL MODELING OF MOAL EXPRESSION |
US11610644B2 (en) | 2014-10-24 | 2023-03-21 | Koninklijke Philips N.V. | Superior bioinformatics process for identifying at risk subject populations |
CA2975328A1 (en) | 2015-01-30 | 2016-08-04 | Envirologix Inc. | Substrates for a nicking and extension reaction |
WO2016126253A1 (en) | 2015-02-05 | 2016-08-11 | The Penn State Research Foundation | Nano-pore arrays for bio-medical, environmental, and industrial sorting, filtering, monitoring, or dispensing |
WO2016166800A1 (en) * | 2015-04-13 | 2016-10-20 | 国立研究開発法人産業技術総合研究所 | Experimental data recording device, computer program, experimental data, experimental data recording method, experimental data display device and experimental data display method |
GB201512869D0 (en) | 2015-07-21 | 2015-09-02 | Almac Diagnostics Ltd | Gene signature for minute therapies |
CN108136051A (en) | 2015-08-04 | 2018-06-08 | Cd诊断股份有限公司 | The method for detecting bad local organization reaction (ALTR) necrosis |
KR102618536B1 (en) * | 2015-08-12 | 2023-12-27 | 삼성전자주식회사 | Method and device for mutation prioritization for personalized therapy of one or more patients |
US10720227B2 (en) * | 2015-08-12 | 2020-07-21 | Samsung Electronics Co., Ltd. | Method and device for mutation prioritization for personalized therapy |
ES2861400T3 (en) | 2015-08-14 | 2021-10-06 | Koninklijke Philips Nv | Evaluation of the activity of the NFkB cell signaling pathway using mathematical models of target gene expression |
US20180305748A1 (en) | 2015-10-18 | 2018-10-25 | Affymetrix, Inc. | Multiallelic Genotyping of Single Nucleotide Polymorphisms and Indels |
CA3005119A1 (en) | 2015-11-19 | 2017-05-26 | Myriad Genetics, Inc. | Signatures for predicting cancer immune therapy response |
US9836444B2 (en) * | 2015-12-10 | 2017-12-05 | International Business Machines Corporation | Spread cell value visualization |
CA3010240A1 (en) | 2016-01-06 | 2017-07-13 | Alexander Gutin | Genes and gene signatures for diagnosis and treatment of melanoma |
US20190128895A1 (en) | 2016-04-20 | 2019-05-02 | Ldx Prognostics Limited Co. | Methods and compositions for prognosing preterm birth |
WO2017193062A1 (en) | 2016-05-06 | 2017-11-09 | Myriad Genetics, Inc. | Gene signatures for renal cancer prognosis |
JP6691617B2 (en) | 2016-05-17 | 2020-04-28 | エルディエックス・プログノスティクス・リミテッド・カンパニーLdx Prognostics Limited Co. | Methods and compositions for providing an assessment of preeclampsia |
CN106066948B (en) * | 2016-06-07 | 2018-09-28 | 北京大学 | A kind of gene expression amount shows method and device |
US20190229959A1 (en) * | 2016-09-27 | 2019-07-25 | Bae Systems Information And Electronic Systems Integration Inc. | Techniques for implementing a portable spectrum analyzer |
US20180165414A1 (en) * | 2016-12-14 | 2018-06-14 | FlowJo, LLC | Applied Computer Technology for Management, Synthesis, Visualization, and Exploration of Parameters in Large Multi-Parameter Data Sets |
KR102116178B1 (en) | 2017-05-10 | 2020-05-27 | 서울대학교산학협력단 | Biomarker for monitoring or detecting early onset of liver cancer from patient having high risk of liver cancer and its use |
WO2018217933A1 (en) | 2017-05-25 | 2018-11-29 | FlowJo, LLC | Visualization, comparative analysis, and automated difference detection for large multi-parameter data sets |
EP3461915A1 (en) | 2017-10-02 | 2019-04-03 | Koninklijke Philips N.V. | Assessment of jak-stat1/2 cellular signaling pathway activity using mathematical modelling of target gene expression |
EP3502279A1 (en) | 2017-12-20 | 2019-06-26 | Koninklijke Philips N.V. | Assessment of mapk-ap 1 cellular signaling pathway activity using mathematical modelling of target gene expression |
WO2019126472A1 (en) | 2017-12-22 | 2019-06-27 | Genentech, Inc. | Use of pilra binding agents for treatment of a disease |
GB2574582A (en) * | 2018-05-28 | 2019-12-18 | Rainer Gabriel Schweiger Martin | Method for simulating a technical device |
US20210269862A1 (en) | 2018-06-18 | 2021-09-02 | Igenomix, S.L. | Methods for assessing endometrial transformation |
CA3115922A1 (en) | 2018-10-09 | 2020-04-16 | Genecentric Therapeutics, Inc. | Detecting cancer cell of origin |
MX2021006234A (en) | 2018-11-30 | 2021-09-10 | Caris Mpi Inc | Next-generation molecular profiling. |
JP2022529294A (en) | 2019-04-17 | 2022-06-20 | アイジェノミクス、ソシエダッド、リミターダ | Improved methods for early diagnosis of uterine leiomyoma and leiomyoma |
IL293489A (en) | 2019-12-02 | 2022-08-01 | Caris Mpi Inc | Pan-cancer platinum response predictor |
WO2023178295A1 (en) | 2022-03-18 | 2023-09-21 | Ludwig Institute For Cancer Research Ltd | Methods and systems for analyzing chromatins |
Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6108635A (en) * | 1996-05-22 | 2000-08-22 | Interleukin Genetics, Inc. | Integrated disease information system |
US6205447B1 (en) * | 1997-06-30 | 2001-03-20 | International Business Machines Corporation | Relational database management of multi-dimensional data |
US20020062258A1 (en) * | 2000-05-18 | 2002-05-23 | Bailey Steven C. | Computer-implemented procurement of items using parametric searching |
US6421612B1 (en) * | 1996-11-04 | 2002-07-16 | 3-Dimensional Pharmaceuticals Inc. | System, method and computer program product for identifying chemical compounds having desired properties |
US20020169788A1 (en) * | 2000-02-16 | 2002-11-14 | Wang-Chien Lee | System and method for automatic loading of an XML document defined by a document-type definition into a relational database including the generation of a relational schema therefor |
US20030108910A1 (en) * | 2001-07-27 | 2003-06-12 | Toland Amanda E. | STK15 (STK6) gene polymorphism and methods of determining cancer risk |
US20030126139A1 (en) * | 2001-12-28 | 2003-07-03 | Lee Timothy A. | System and method for loading commercial web sites |
Family Cites Families (64)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4683202A (en) | 1985-03-28 | 1987-07-28 | Cetus Corporation | Process for amplifying nucleic acid sequences |
NO870613L (en) | 1986-03-05 | 1987-09-07 | Molecular Diagnostics Inc | DETECTION OF MICROORGANISMS IN A SAMPLE CONTAINING NUCLEIC ACID. |
US4740611A (en) * | 1986-10-30 | 1988-04-26 | The Standard Oil Company | N,N'-disubstituted ureas |
US4705864A (en) * | 1986-11-10 | 1987-11-10 | The Standard Oil Company | Aryl oxime derivatives of hydantoins |
WO1988004670A1 (en) | 1986-12-20 | 1988-06-30 | Kukita, Takeshi | Bilirubin antigen, monoclonal antibody therefor, process for their preparation, and their use |
US5525464A (en) | 1987-04-01 | 1996-06-11 | Hyseq, Inc. | Method of sequencing by hybridization of oligonucleotide probes |
US5202231A (en) | 1987-04-01 | 1993-04-13 | Drmanac Radoje T | Method of sequencing of genomes by hybridization of oligonucleotide probes |
US5700637A (en) | 1988-05-03 | 1997-12-23 | Isis Innovation Limited | Apparatus and method for analyzing polynucleotide sequences and method of generating oligonucleotide arrays |
DE68928853T2 (en) | 1988-05-20 | 1999-08-05 | Cetus Corp | FASTENING OF SEQUENCE-SPECIFIC SAMPLES |
US5206137A (en) * | 1988-09-08 | 1993-04-27 | Lifecodes Corporation | Compositions and methods useful for genetic analysis |
US6203977B1 (en) * | 1988-11-15 | 2001-03-20 | Yale University | Delineation of individual human chromosomes in metaphase and interphase cells by in situ suppression hybridization |
JPH02299598A (en) | 1989-04-14 | 1990-12-11 | Ro Inst For Molecular Genetics & Geneteic Res | Determination by means of hybridization, together with oligonucleotide probe of all or part of extremely short sequence in sample of nucleic acid connecting with separate particle of microscopic size |
US5143854A (en) | 1989-06-07 | 1992-09-01 | Affymax Technologies N.V. | Large scale photolithographic solid phase synthesis of polypeptides and receptor binding screening thereof |
US5800992A (en) * | 1989-06-07 | 1998-09-01 | Fodor; Stephen P.A. | Method of detecting nucleic acids |
US5871928A (en) * | 1989-06-07 | 1999-02-16 | Fodor; Stephen P. A. | Methods for nucleic acid analysis |
US6040138A (en) | 1995-09-15 | 2000-03-21 | Affymetrix, Inc. | Expression monitoring by hybridization to high density oligonucleotide arrays |
US5925525A (en) * | 1989-06-07 | 1999-07-20 | Affymetrix, Inc. | Method of identifying nucleotide differences |
EP0834576B1 (en) | 1990-12-06 | 2002-01-16 | Affymetrix, Inc. (a Delaware Corporation) | Detection of nucleic acid sequences |
ATE244065T1 (en) | 1990-12-06 | 2003-07-15 | Affymetrix Inc | METHODS AND REAGENTS FOR VERY LARGE SCALE IMMOBILIZED POLYMER SYNTHESIS |
GR1000797B (en) | 1991-06-10 | 1993-01-25 | Emmanouil E Petromanolakis | Wave-making energy absorber during vessel s propulsion |
AU663101B2 (en) * | 1991-08-13 | 1995-09-28 | Wisconsin Milk Marketing Board | DNA sequence encoding bovine alpha-lactalbumin and methods of use |
US5846717A (en) * | 1996-01-24 | 1998-12-08 | Third Wave Technologies, Inc. | Detection of nucleic acid sequences by invader-directed cleavage |
JP2001507921A (en) | 1992-04-27 | 2001-06-19 | トラスティーズ オブ ダートマス カレッジ | Detection of gene sequences in biological fluids |
US6251920B1 (en) * | 1993-05-13 | 2001-06-26 | Neorx Corporation | Prevention and treatment of cardiovascular pathologies |
US6395494B1 (en) * | 1993-05-13 | 2002-05-28 | Neorx Corporation | Method to determine TGF-β |
US5524070A (en) * | 1992-10-07 | 1996-06-04 | The Research Foundation Of State University Of New York | Local adaptive contrast enhancement |
US5632282A (en) * | 1993-07-20 | 1997-05-27 | Hay; S. Hutson | Ocular disease detection apparatus |
EP0730663B1 (en) | 1993-10-26 | 2003-09-24 | Affymetrix, Inc. | Arrays of nucleic acid probes on biological chips |
DK0725682T3 (en) | 1993-10-28 | 2002-07-15 | Houston Advanced Res Ct | Micro-made, porous pass-through apparatus for discrete detection of bonding reactions |
US6096503A (en) * | 1993-11-12 | 2000-08-01 | The Scripps Research Institute | Method for simultaneous identification of differentially expresses mRNAs and measurement of relative concentrations |
US6339767B1 (en) * | 1997-06-02 | 2002-01-15 | Aurigin Systems, Inc. | Using hyperbolic trees to visualize data generated by patent-centric and group-oriented data processing |
EP0667586A3 (en) * | 1994-02-14 | 1996-08-28 | Digital Equipment Corp | Database generator. |
US5560005A (en) * | 1994-02-25 | 1996-09-24 | Actamed Corp. | Methods and systems for object-based relational distributed databases |
US5571639A (en) * | 1994-05-24 | 1996-11-05 | Affymax Technologies N.V. | Computer-aided engineering system for design of sequence arrays and lithographic masks |
US5570291A (en) * | 1994-08-24 | 1996-10-29 | Wallace Computer Services, Inc. | Custom product estimating and order processing system |
US6600996B2 (en) | 1994-10-21 | 2003-07-29 | Affymetrix, Inc. | Computer-aided techniques for analyzing biological sequences |
US5795716A (en) | 1994-10-21 | 1998-08-18 | Chee; Mark S. | Computer-aided visualization and analysis system for sequence evaluation |
EP0805874A4 (en) | 1995-01-27 | 1998-05-20 | Incyte Pharma Inc | Computer system storing and analyzing microbiological data |
US5961923A (en) * | 1995-04-25 | 1999-10-05 | Irori | Matrices with memories and uses thereof |
EP0747418B1 (en) * | 1995-06-06 | 2002-07-03 | Ube Industries, Ltd. | Aromatic polyimide and gas separation |
US5707806A (en) | 1995-06-07 | 1998-01-13 | Genzyme Corporation | Direct sequence identification of mutations by cleavage- and ligation-associated mutation-specific sequencing |
US5777888A (en) | 1995-08-09 | 1998-07-07 | Regents Of The University Of California | Systems for generating and analyzing stimulus-response output signal matrices |
US5871697A (en) | 1995-10-24 | 1999-02-16 | Curagen Corporation | Method and apparatus for identifying, classifying, or quantifying DNA sequences in a sample without sequencing |
GB9522615D0 (en) | 1995-11-03 | 1996-01-03 | Pharmacia Spa | 4-Phenyl-4-oxo-butanoic acid derivatives with kynurenine-3-hydroxylase inhibiting activity |
US5778200A (en) | 1995-11-21 | 1998-07-07 | Advanced Micro Devices, Inc. | Bus arbiter including aging factor counters to dynamically vary arbitration priority |
JP2002515738A (en) | 1996-01-23 | 2002-05-28 | アフィメトリックス,インコーポレイティド | Nucleic acid analysis |
AU2189397A (en) | 1996-02-08 | 1997-08-28 | Affymetrix, Inc. | Chip-based speciation and phenotypic characterization of microorganisms |
US5989835A (en) * | 1997-02-27 | 1999-11-23 | Cellomics, Inc. | System for cell-based screening |
US5968784A (en) * | 1997-01-15 | 1999-10-19 | Chugai Pharmaceutical Co., Ltd. | Method for analyzing quantitative expression of genes |
DE69823206T2 (en) * | 1997-07-25 | 2004-08-19 | Affymetrix, Inc. (a Delaware Corp.), Santa Clara | METHOD FOR PRODUCING A BIO-INFORMATICS DATABASE |
US6032151A (en) * | 1997-11-17 | 2000-02-29 | Sun Microsystems, Inc. | Database system employing polymorphic entry and entry matching |
US6025194A (en) * | 1997-11-19 | 2000-02-15 | Geron Corporation | Nucleic acid sequence of senescence asssociated gene |
US5991766A (en) * | 1997-12-02 | 1999-11-23 | Electronic Data Systems Corporation | Method and system for managing redundant objects in a distributed object system |
US20030036855A1 (en) * | 1998-03-16 | 2003-02-20 | Praelux Incorporated, A Corporation Of New Jersey | Method and apparatus for screening chemical compounds |
US6324533B1 (en) * | 1998-05-29 | 2001-11-27 | International Business Machines Corporation | Integrated database and data-mining system |
AU2342900A (en) * | 1998-09-23 | 2000-05-01 | Cleveland Clinic Foundation, The | Novel interferon stimulated and repressed genes |
US6140054A (en) * | 1998-09-30 | 2000-10-31 | University Of Utah Research Foundation | Multiplex genotyping using fluorescent hybridization probes |
US6251601B1 (en) * | 1999-02-02 | 2001-06-26 | Vysis, Inc. | Simultaneous measurement of gene expression and genomic abnormalities using nucleic acid microarrays |
US6284465B1 (en) * | 1999-04-15 | 2001-09-04 | Agilent Technologies, Inc. | Apparatus, systems and method for locating nucleic acids bound to surfaces |
US6338071B1 (en) * | 1999-08-18 | 2002-01-08 | Affymetrix, Inc. | Method and system for providing a contract management system using an action-item table |
US6754666B1 (en) * | 1999-08-19 | 2004-06-22 | A2I, Inc. | Efficient storage and access in a database management system |
AU6909300A (en) * | 1999-08-20 | 2001-03-19 | Merck & Co., Inc. | Substituted ureas as cell adhesion inhibitors |
US6569615B1 (en) * | 2000-04-10 | 2003-05-27 | The United States Of America As Represented By The Department Of Veteran's Affairs | Composition and methods for tissue preservation |
US7731904B2 (en) * | 2000-09-19 | 2010-06-08 | Canon Kabushiki Kaisha | Method for making probe support and apparatus used for the method |
-
1998
- 1998-07-24 DE DE69823206T patent/DE69823206T2/en not_active Expired - Lifetime
- 1998-07-24 US US09/122,304 patent/US6188783B1/en not_active Expired - Lifetime
- 1998-07-24 WO PCT/US1998/015456 patent/WO1999005574A1/en active Application Filing
- 1998-07-24 US US09/122,434 patent/US6308170B1/en not_active Expired - Lifetime
- 1998-07-24 AT AT98936012T patent/ATE264523T1/en not_active IP Right Cessation
- 1998-07-24 WO PCT/US1998/015151 patent/WO1999005323A1/en not_active Application Discontinuation
- 1998-07-24 WO PCT/US1998/015469 patent/WO1999005591A2/en active IP Right Grant
- 1998-07-24 WO PCT/US1998/015458 patent/WO1999005324A1/en active Application Filing
- 1998-07-24 EP EP98936972A patent/EP1009861A4/en not_active Withdrawn
- 1998-07-24 EP EP98936012A patent/EP1002264B1/en not_active Expired - Lifetime
- 1998-07-24 JP JP2000504291A patent/JP2001515234A/en active Pending
- 1998-07-24 EP EP98937126A patent/EP0998697A4/en not_active Withdrawn
- 1998-07-24 EP EP98937128A patent/EP1007737A4/en not_active Withdrawn
- 1998-07-24 US US09/122,167 patent/US6229911B1/en not_active Expired - Lifetime
- 1998-07-24 JP JP2000504290A patent/JP3776728B2/en not_active Expired - Lifetime
- 1998-07-24 US US09/122,169 patent/US6484183B1/en not_active Expired - Lifetime
- 1998-07-24 JP JP2000504502A patent/JP2001511529A/en not_active Ceased
- 1998-07-24 JP JP2000504489A patent/JP2001511550A/en active Pending
-
2001
- 2001-04-16 US US09/836,867 patent/US6567540B2/en not_active Expired - Lifetime
- 2001-08-27 US US09/940,285 patent/US6532462B2/en not_active Expired - Lifetime
-
2002
- 2002-08-14 US US10/219,021 patent/US20030074363A1/en not_active Abandoned
-
2003
- 2003-02-25 US US10/374,170 patent/US6882742B2/en not_active Expired - Lifetime
-
2004
- 2004-09-02 JP JP2004256352A patent/JP2005100389A/en not_active Withdrawn
-
2005
- 2005-01-18 US US11/038,624 patent/US20050164270A1/en not_active Abandoned
- 2005-03-14 US US11/080,216 patent/US7215804B2/en not_active Expired - Fee Related
- 2005-05-30 JP JP2005158223A patent/JP2005353057A/en active Pending
Patent Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6108635A (en) * | 1996-05-22 | 2000-08-22 | Interleukin Genetics, Inc. | Integrated disease information system |
US6421612B1 (en) * | 1996-11-04 | 2002-07-16 | 3-Dimensional Pharmaceuticals Inc. | System, method and computer program product for identifying chemical compounds having desired properties |
US6205447B1 (en) * | 1997-06-30 | 2001-03-20 | International Business Machines Corporation | Relational database management of multi-dimensional data |
US20020169788A1 (en) * | 2000-02-16 | 2002-11-14 | Wang-Chien Lee | System and method for automatic loading of an XML document defined by a document-type definition into a relational database including the generation of a relational schema therefor |
US20020062258A1 (en) * | 2000-05-18 | 2002-05-23 | Bailey Steven C. | Computer-implemented procurement of items using parametric searching |
US6820076B2 (en) * | 2000-05-18 | 2004-11-16 | I2 Technologies Us, Inc. | Database system facilitating parametric searching |
US20030108910A1 (en) * | 2001-07-27 | 2003-06-12 | Toland Amanda E. | STK15 (STK6) gene polymorphism and methods of determining cancer risk |
US20030126139A1 (en) * | 2001-12-28 | 2003-07-03 | Lee Timothy A. | System and method for loading commercial web sites |
Cited By (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20070128647A1 (en) * | 2005-12-07 | 2007-06-07 | Affymetrix, Inc. | Methods for high throughput genotyping |
US7634363B2 (en) | 2005-12-07 | 2009-12-15 | Affymetrix, Inc. | Methods for high throughput genotyping |
US7991564B2 (en) | 2005-12-07 | 2011-08-02 | Affymetrix, Inc. | Methods for high throughput genotyping |
US8498825B2 (en) | 2005-12-07 | 2013-07-30 | Affymetrix, Inc. | Methods for high throughput genotyping |
US20080287308A1 (en) * | 2007-05-18 | 2008-11-20 | Affymetrix, Inc. | System, method, and computer software product for genotype determination using probe array data |
US8200440B2 (en) | 2007-05-18 | 2012-06-12 | Affymetrix, Inc. | System, method, and computer software product for genotype determination using probe array data |
US9760675B2 (en) | 2007-05-18 | 2017-09-12 | Affymetrix, Inc. | System, method, and computer software product for genotype determination using probe array data |
US10832796B2 (en) | 2007-05-18 | 2020-11-10 | Affymetrix, Inc. | System, method, and computer software product for genotype determination using probe array data |
Also Published As
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US20050164270A1 (en) | Methods and system for providing a polymorphism database | |
US6826296B2 (en) | Method and system for providing a probe array chip design database | |
US6185561B1 (en) | Method and apparatus for providing and expression data mining database | |
Gibbs et al. | The international HapMap project | |
National Research Council | DNA technology in forensic science | |
US20030220844A1 (en) | Method and system for purchasing genetic data | |
US20030028501A1 (en) | Computer based method for providing a laboratory information management system | |
US20060212229A1 (en) | Method and system for providing a probe array chip design database | |
Charru et al. | HYPERGENE: a clinical and genetic database for genetic analysis of human hypertension | |
US20040199544A1 (en) | Method and apparatus for providing an expression data mining database | |
WO2000016220A9 (en) | Method and apparatus for providing an expression data mining database and laboratory information management | |
US20060259251A1 (en) | Computer software products for associating gene expression with genetic variations | |
EP1396800A2 (en) | Method and apparatus for providing a bioinformatics database | |
JP2003526133A6 (en) | Method and apparatus for providing expression data mining database and laboratory information management | |
JP2003526133A (en) | Method and apparatus for providing expression data mining database and laboratory information management | |
EP1038245A1 (en) | Method and apparatus for providing an expression data mining database and laboratory information management | |
Grant | A Microarray Database | |
Carroll | Mobile elements: Genome-wide distribution and complexity | |
Human | The International HapMap Project | |
National Research Council (US) Committee on Human Genome Diversity | Sampling Issues |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
STCB | Information on status: application discontinuation |
Free format text: ABANDONED -- FAILURE TO RESPOND TO AN OFFICE ACTION |