Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2009-01

AUTHORS

Da Wei Huang, Brad T Sherman, Richard A Lempicki

ABSTRACT

DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies. More... »

PAGES

44

Journal

TITLE

Nature Protocols

ISSUE

1

VOLUME

4

Related Patents

  • Inhibitors Of Cacna1a/Alpha1a Subunit Internal Ribosomal Entry Site (Ires) And Methods Of Treating Spinocerebellar Ataxia Type 6
  • Method And System For Extraction And Normalization Of Relationships Via Ontology Induction
  • Systems For Computer Network Security Risk Assessment Including User Compromise Analysis Associated With A Network Of Devices
  • Computer-Implemented Systems And Methods For Data Management And Visualization
  • Combinations Of Mdm2 Inhibitors And Bcl-Xl Inhibitors
  • Schematic And Database Linking System
  • Systems For Network Risk Assessment Including Processing Of User Access Rights Associated With A Network Of Devices
  • Network Anomaly Detection
  • Biomarkers For Lung Neuroendocrine Tumors
  • Biomarkers For Early Diagnosis Of Alzheimer's Disease
  • Time-Sensitive Cube
  • Microrna Treatment Of Fibrosis
  • Taf1 Inhibitors For The Therapy Of Cancer
  • Systems And User Interfaces For Dynamic And Interactive Investigation Of Bad Actor Behavior Based On Automatic Clustering Of Related Data In Various Data Structures
  • Systems And Interactive User Interfaces For Automatic Generation Of Temporal Representation Of Data Objects
  • Compositions And Methods For Treatment Of Melanoma
  • Systems And Methods For Organizing And Identifying Documents Via Hierarchies And Dimensions Of Tags
  • Methods And Biomarkers For Analysis Of Colorectal Cancer
  • System And Method Of Generating Data Points From One Or More Data Stores Of Data Items For Chart Creation And Manipulation
  • Alteration Of Neuronal Gene Expression By Synthetic Pirnas And By Alteration Of Pirna Function
  • Genetic Markers Associated With Asd And Other Childhood Developmental Delay Disorders
  • Muscle Secretome And Uses Thereof
  • Compositions And Methods For Inhibiting Human Host Factors Required For Influenza Virus Replication
  • Generating Object Time Series And Data Objects
  • Interactive Data Object Map
  • System For Providing Dynamic Linked Panels In User Interface
  • Methods Of Treating Cancer Patients Responding To Ezh2 Inhibitor Gsk126
  • Synergistic Combinations Of Ox40l Antibodies For The Treatment Of Gvhd
  • Therapy For Mll-Rearranged Leukemia
  • Differentiation Into Brown Adipocytes
  • Systems And User Interfaces For Holistic, Data-Driven Investigation Of Bad Actor Behavior Based On Clustering And Scoring Of Related Data
  • Human Pluripotent Stem Cell-Based Models For Predictive Developmental Neural Toxicity
  • Interactive User Interfaces For Location-Based Data Analysis
  • System And Method For Parameterizing Documents For Automatic Workflow Generation
  • Modulation Of Cardiac Stem-Progenitor Cell Differentiation, Assays And Uses Thereof
  • Methods For Increasing Immune Responses Using Agents That Directly Bind To And Activate Ire-1
  • Methods Of Derivation And/Or Propagation Of Epithelial Cells
  • Compositions And Methods For Epithelial Stem Cell Expansion And Culture
  • Mobile Reports
  • Systems And Methods For Automatic And Customizable Data Minimization Of Electronic Data Stores
  • Oligonucleotide Compositions And Uses Thereof
  • Molecular Signature Of Hepatocellular Carcinoma
  • Assays For Massively Combinatorial Perturbation Profiling And Cellular Circuit Reconstruction
  • System And Method For Generating Event Visualizations
  • Microbiome Response To Agents
  • Gene Expression Panel For Breast Cancer Prognosis
  • Interactive User Interface For Dynamic Data Analysis Exploration And Query Processing
  • Network Anomaly Detection
  • Methods, Systems And Kits For Predicting Viral Set Point
  • Interactive User Interface For Dynamic Data Analysis Exploration And Query Processing
  • Data Aggregation And Analysis System
  • Mir-155 Inhibitors For Treating Cutaneous T Cell Lymphoma (Ctcl)
  • Systems For Network Risk Assessment Including Processing Of User Access Rights Associated With A Network Of Devices
  • Computer-Implemented Systems And Methods For Data Management And Visualization
  • Systems And User Interfaces For Dynamic And Interactive Simultaneous Querying Of Multiple Data Stores
  • Use Of Teams In A Mobile Application
  • Compounds For Inducing Anti-Tumor Immunity And Methods Thereof
  • Methods And Compositions For Obtaining Useful Plant Traits
  • Modal-Less Interface Enhancements
  • Biomarkers For The Detection Of Frontotemporal Dementia
  • Method For Classifying Tumour Cells
  • Mirna
  • Compounds For Inducing Anti-Tumor Immunity And Methods Thereof
  • Immortalized Mesenchymal Stromal Cell From Adipose Tissue
  • Tactical Security System
  • Simple Web Search
  • Compositions And Methods For Epithelial Stem Cell Expansion And Culture
  • System And Method For Batch Evaluation Programs
  • External Malware Data Item Clustering And Analysis
  • Tactical Security System
  • Detection Of Oxidized Polypeptides
  • Time-Series Analysis System
  • Synergistic Combinations Of Ox40l Antibodies For The Treatment Of Gvhd
  • System For Providing Dynamic Linked Panels In User Interface
  • Targeting Metabolic Enzymes In Human Cancer
  • Malicious Software Detection In A Computing System
  • Generating Object Time Series From Data Objects
  • Network Anomaly Detection
  • Systems For Network Risk Assessment Including Processing Of User Access Rights Associated With A Network Of Devices
  • Diagnosis And Treatment Of Metabolic Disorders
  • Systems And User Interfaces For Dynamic And Interactive Access Of, Investigation Of, And Analysis Of Data Objects Stored In One Or More Databases
  • Network Intrusion Data Item Clustering And Analysis
  • Interactive Geospatial Map
  • Antisense Oligonucleotides Targeting 3'Utr Region Of A20
  • Concept Indexing Among Database Of Documents Using Machine Learning Techniques
  • Surface Markers For The Isolation Of Myogenic Stem/Progenitor Cells
  • Unwanted Tunneling Alert System
  • Alternatively Spliced Mrna Isoforms As Prognostic Indicators For Metastatic Cancer
  • Systems For Network Risk Assessment Including Processing Of User Access Rights Associated With A Network Of Devices
  • Systems And Methods For Key Phrase Characterization Of Documents
  • Method Of Producing Renal Cells From Fibroblasts
  • Gene Expression Profile In Diagnostics
  • Long-Term Self-Renewing Neural Stem Cells
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/nprot.2008.211

    DOI

    http://dx.doi.org/10.1038/nprot.2008.211

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1039987283

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/19131956


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0604", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Genetics", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/06", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Biological Sciences", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Computational Biology", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Data Interpretation, Statistical", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Genes", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Genomics", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Internet", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Software", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "name": [
                "Laboratory of Immunopathogenesis and Bioinformatics, Clinical Services Program, SAIC-Frederick Inc., National Cancer Institute at Frederick, Frederick, Maryland 21702, USA."
              ], 
              "type": "Organization"
            }, 
            "familyName": "Da Wei Huang", 
            "id": "sg:person.011667644635.83", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011667644635.83"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Laboratory of Immunopathogenesis and Bioinformatics, Clinical Services Program, SAIC-Frederick Inc., National Cancer Institute at Frederick, Frederick, Maryland 21702, USA."
              ], 
              "type": "Organization"
            }, 
            "familyName": "Sherman", 
            "givenName": "Brad T", 
            "id": "sg:person.01322514467.55", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01322514467.55"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Laboratory of Immunopathogenesis and Bioinformatics, Clinical Services Program, SAIC-Frederick Inc., National Cancer Institute at Frederick, Frederick, Maryland 21702, USA."
              ], 
              "type": "Organization"
            }, 
            "familyName": "Lempicki", 
            "givenName": "Richard A", 
            "id": "sg:person.0716662073.55", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0716662073.55"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1186/gb-2003-4-10-r70", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001293245", 
              "https://doi.org/10.1186/gb-2003-4-10-r70"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btg455", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001761938"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkm415", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003264848"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkh409", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015906494"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2105-6-189", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016524045", 
              "https://doi.org/10.1186/1471-2105-6-189"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2105-6-189", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016524045", 
              "https://doi.org/10.1186/1471-2105-6-189"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/gb-2003-4-5-p3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021292424", 
              "https://doi.org/10.1186/gb-2003-4-5-p3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/bth088", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022171874"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/gb-2007-8-9-r183", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027884417", 
              "https://doi.org/10.1186/gb-2007-8-9-r183"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1073/pnas.142287999", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027915405"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/gb-2004-5-12-r101", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1030306020", 
              "https://doi.org/10.1186/gb-2004-5-12-r101"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gki454", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033041691"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1073/pnas.0506580102", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037705714"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1073/pnas.0506580102", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037705714"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2105-8-426", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037731520", 
              "https://doi.org/10.1186/1471-2105-8-426"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2105-8-426", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037731520", 
              "https://doi.org/10.1186/1471-2105-8-426"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2105-6-168", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047729779", 
              "https://doi.org/10.1186/1471-2105-6-168"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/bti565", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050298763"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.6026/97320630002428", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1073593888"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2009-01", 
        "datePublishedReg": "2009-01-01", 
        "description": "DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1038/nprot.2008.211", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isFundedItemOf": [
          {
            "id": "sg:grant.2427747", 
            "type": "MonetaryGrant"
          }
        ], 
        "isPartOf": [
          {
            "id": "sg:journal.1037502", 
            "issn": [
              "1754-2189", 
              "1750-2799"
            ], 
            "name": "Nature Protocols", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "1", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "4"
          }
        ], 
        "name": "Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources", 
        "pagination": "44", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "be7ba210f9eb9661b068cedd2c95dddc0aaf89057fdc8ccbbcc4557099756304"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "19131956"
            ]
          }, 
          {
            "name": "nlm_unique_id", 
            "type": "PropertyValue", 
            "value": [
              "101284307"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1038/nprot.2008.211"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1039987283"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1038/nprot.2008.211", 
          "https://app.dimensions.ai/details/publication/pub.1039987283"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-10T13:00", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8659_00000429.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://www.nature.com/articles/nprot.2008.211"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/nprot.2008.211'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/nprot.2008.211'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/nprot.2008.211'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/nprot.2008.211'


     

    This table displays all metadata directly associated to this object as RDF triples.

    166 TRIPLES      21 PREDICATES      51 URIs      27 LITERALS      15 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1038/nprot.2008.211 schema:about N4e78b13a120b4fdaa98d6efc52f3c9fb
    2 N50865f7b77854e7fb2ea4e2151cd0885
    3 N872306276a864d7a9100a5cc7f2de35b
    4 N9115134ba6ac462fb3f35a3ae310f9be
    5 Nc08d099eb2ba4d4c9e9ca7238b430176
    6 Nf546a78c461a42208f0d19fe5e264e3a
    7 anzsrc-for:06
    8 anzsrc-for:0604
    9 schema:author N861b4671af23424b9f28aa05f55379ab
    10 schema:citation sg:pub.10.1186/1471-2105-6-168
    11 sg:pub.10.1186/1471-2105-6-189
    12 sg:pub.10.1186/1471-2105-8-426
    13 sg:pub.10.1186/gb-2003-4-10-r70
    14 sg:pub.10.1186/gb-2003-4-5-p3
    15 sg:pub.10.1186/gb-2004-5-12-r101
    16 sg:pub.10.1186/gb-2007-8-9-r183
    17 https://doi.org/10.1073/pnas.0506580102
    18 https://doi.org/10.1073/pnas.142287999
    19 https://doi.org/10.1093/bioinformatics/btg455
    20 https://doi.org/10.1093/bioinformatics/bth088
    21 https://doi.org/10.1093/bioinformatics/bti565
    22 https://doi.org/10.1093/nar/gkh409
    23 https://doi.org/10.1093/nar/gki454
    24 https://doi.org/10.1093/nar/gkm415
    25 https://doi.org/10.6026/97320630002428
    26 schema:datePublished 2009-01
    27 schema:datePublishedReg 2009-01-01
    28 schema:description DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
    29 schema:genre research_article
    30 schema:inLanguage en
    31 schema:isAccessibleForFree false
    32 schema:isPartOf N6f91aebf299549b18eb94d730628391b
    33 Ndaf4c3ffd213418cb268dfdd69ba4df4
    34 sg:journal.1037502
    35 schema:name Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources
    36 schema:pagination 44
    37 schema:productId N02802e8ac1144e6fb1da168ee7cd9db1
    38 N6a0212fd7d00470d8e2b5a3d7037980c
    39 N8872cbc627f149359980382607f24433
    40 Ne45fa7c41ca34384860604ca4ca8f1e9
    41 Nf4135773946443a98142ebcdd58c8507
    42 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039987283
    43 https://doi.org/10.1038/nprot.2008.211
    44 schema:sdDatePublished 2019-04-10T13:00
    45 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    46 schema:sdPublisher N6191d5f845e54f03b03f5407cd3100ca
    47 schema:url https://www.nature.com/articles/nprot.2008.211
    48 sgo:license sg:explorer/license/
    49 sgo:sdDataset articles
    50 rdf:type schema:ScholarlyArticle
    51 N02802e8ac1144e6fb1da168ee7cd9db1 schema:name doi
    52 schema:value 10.1038/nprot.2008.211
    53 rdf:type schema:PropertyValue
    54 N4e78b13a120b4fdaa98d6efc52f3c9fb schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    55 schema:name Internet
    56 rdf:type schema:DefinedTerm
    57 N50865f7b77854e7fb2ea4e2151cd0885 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    58 schema:name Genomics
    59 rdf:type schema:DefinedTerm
    60 N6191d5f845e54f03b03f5407cd3100ca schema:name Springer Nature - SN SciGraph project
    61 rdf:type schema:Organization
    62 N6a0212fd7d00470d8e2b5a3d7037980c schema:name dimensions_id
    63 schema:value pub.1039987283
    64 rdf:type schema:PropertyValue
    65 N6f91aebf299549b18eb94d730628391b schema:volumeNumber 4
    66 rdf:type schema:PublicationVolume
    67 N861b4671af23424b9f28aa05f55379ab rdf:first sg:person.011667644635.83
    68 rdf:rest Nc5167e02446641dea071058fede0f718
    69 N872306276a864d7a9100a5cc7f2de35b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    70 schema:name Genes
    71 rdf:type schema:DefinedTerm
    72 N8872cbc627f149359980382607f24433 schema:name pubmed_id
    73 schema:value 19131956
    74 rdf:type schema:PropertyValue
    75 N8fd040e28a7f4e80b9e6b1320c301e64 rdf:first sg:person.0716662073.55
    76 rdf:rest rdf:nil
    77 N9115134ba6ac462fb3f35a3ae310f9be schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    78 schema:name Computational Biology
    79 rdf:type schema:DefinedTerm
    80 N9d3ed4a302204bda86a99398824b1bc6 schema:name Laboratory of Immunopathogenesis and Bioinformatics, Clinical Services Program, SAIC-Frederick Inc., National Cancer Institute at Frederick, Frederick, Maryland 21702, USA.
    81 rdf:type schema:Organization
    82 Nbf707f6e9a5a4ec4bdfbee7871f563aa schema:name Laboratory of Immunopathogenesis and Bioinformatics, Clinical Services Program, SAIC-Frederick Inc., National Cancer Institute at Frederick, Frederick, Maryland 21702, USA.
    83 rdf:type schema:Organization
    84 Nc08d099eb2ba4d4c9e9ca7238b430176 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    85 schema:name Software
    86 rdf:type schema:DefinedTerm
    87 Nc5167e02446641dea071058fede0f718 rdf:first sg:person.01322514467.55
    88 rdf:rest N8fd040e28a7f4e80b9e6b1320c301e64
    89 Ndaf4c3ffd213418cb268dfdd69ba4df4 schema:issueNumber 1
    90 rdf:type schema:PublicationIssue
    91 Ne45fa7c41ca34384860604ca4ca8f1e9 schema:name readcube_id
    92 schema:value be7ba210f9eb9661b068cedd2c95dddc0aaf89057fdc8ccbbcc4557099756304
    93 rdf:type schema:PropertyValue
    94 Nf4135773946443a98142ebcdd58c8507 schema:name nlm_unique_id
    95 schema:value 101284307
    96 rdf:type schema:PropertyValue
    97 Nf546a78c461a42208f0d19fe5e264e3a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    98 schema:name Data Interpretation, Statistical
    99 rdf:type schema:DefinedTerm
    100 Nf63fde6acf8345ef8ccf3a0d6e63f4c6 schema:name Laboratory of Immunopathogenesis and Bioinformatics, Clinical Services Program, SAIC-Frederick Inc., National Cancer Institute at Frederick, Frederick, Maryland 21702, USA.
    101 rdf:type schema:Organization
    102 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
    103 schema:name Biological Sciences
    104 rdf:type schema:DefinedTerm
    105 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
    106 schema:name Genetics
    107 rdf:type schema:DefinedTerm
    108 sg:grant.2427747 http://pending.schema.org/fundedItem sg:pub.10.1038/nprot.2008.211
    109 rdf:type schema:MonetaryGrant
    110 sg:journal.1037502 schema:issn 1750-2799
    111 1754-2189
    112 schema:name Nature Protocols
    113 rdf:type schema:Periodical
    114 sg:person.011667644635.83 schema:affiliation N9d3ed4a302204bda86a99398824b1bc6
    115 schema:familyName Da Wei Huang
    116 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011667644635.83
    117 rdf:type schema:Person
    118 sg:person.01322514467.55 schema:affiliation Nf63fde6acf8345ef8ccf3a0d6e63f4c6
    119 schema:familyName Sherman
    120 schema:givenName Brad T
    121 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01322514467.55
    122 rdf:type schema:Person
    123 sg:person.0716662073.55 schema:affiliation Nbf707f6e9a5a4ec4bdfbee7871f563aa
    124 schema:familyName Lempicki
    125 schema:givenName Richard A
    126 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0716662073.55
    127 rdf:type schema:Person
    128 sg:pub.10.1186/1471-2105-6-168 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047729779
    129 https://doi.org/10.1186/1471-2105-6-168
    130 rdf:type schema:CreativeWork
    131 sg:pub.10.1186/1471-2105-6-189 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016524045
    132 https://doi.org/10.1186/1471-2105-6-189
    133 rdf:type schema:CreativeWork
    134 sg:pub.10.1186/1471-2105-8-426 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037731520
    135 https://doi.org/10.1186/1471-2105-8-426
    136 rdf:type schema:CreativeWork
    137 sg:pub.10.1186/gb-2003-4-10-r70 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001293245
    138 https://doi.org/10.1186/gb-2003-4-10-r70
    139 rdf:type schema:CreativeWork
    140 sg:pub.10.1186/gb-2003-4-5-p3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021292424
    141 https://doi.org/10.1186/gb-2003-4-5-p3
    142 rdf:type schema:CreativeWork
    143 sg:pub.10.1186/gb-2004-5-12-r101 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030306020
    144 https://doi.org/10.1186/gb-2004-5-12-r101
    145 rdf:type schema:CreativeWork
    146 sg:pub.10.1186/gb-2007-8-9-r183 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027884417
    147 https://doi.org/10.1186/gb-2007-8-9-r183
    148 rdf:type schema:CreativeWork
    149 https://doi.org/10.1073/pnas.0506580102 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037705714
    150 rdf:type schema:CreativeWork
    151 https://doi.org/10.1073/pnas.142287999 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027915405
    152 rdf:type schema:CreativeWork
    153 https://doi.org/10.1093/bioinformatics/btg455 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001761938
    154 rdf:type schema:CreativeWork
    155 https://doi.org/10.1093/bioinformatics/bth088 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022171874
    156 rdf:type schema:CreativeWork
    157 https://doi.org/10.1093/bioinformatics/bti565 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050298763
    158 rdf:type schema:CreativeWork
    159 https://doi.org/10.1093/nar/gkh409 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015906494
    160 rdf:type schema:CreativeWork
    161 https://doi.org/10.1093/nar/gki454 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033041691
    162 rdf:type schema:CreativeWork
    163 https://doi.org/10.1093/nar/gkm415 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003264848
    164 rdf:type schema:CreativeWork
    165 https://doi.org/10.6026/97320630002428 schema:sameAs https://app.dimensions.ai/details/publication/pub.1073593888
    166 rdf:type schema:CreativeWork
     




    Preview window. Press ESC to close (or click here)


    ...