Improving the prediction of the functional impact of cancer mutations by baseline tolerance transformation View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2012-11

AUTHORS

Abel Gonzalez-Perez, Jordi Deu-Pons, Nuria Lopez-Bigas

ABSTRACT

High-throughput prioritization of cancer-causing mutations (drivers) is a key challenge of cancer genome projects, due to the number of somatic variants detected in tumors. One important step in this task is to assess the functional impact of tumor somatic mutations. A number of computational methods have been employed for that purpose, although most were originally developed to distinguish disease-related nonsynonymous single nucleotide variants (nsSNVs) from polymorphisms. Our new method, transformed Functional Impact score for Cancer (transFIC), improves the assessment of the functional impact of tumor nsSNVs by taking into account the baseline tolerance of genes to functional variants. More... »

PAGES

89

References to SciGraph publications

  • 2006-12. SNPs3D: Candidate gene and SNP selection for association studies in BMC BIOINFORMATICS
  • 2010-12. Ensembl variation resources in BMC GENOMICS
  • 2010-04-15. International network of cancer genome projects in NATURE
  • 2012-05. Landscape of TET2 mutations in acute myeloid leukemia in LEUKEMIA
  • 2010-10-28. A map of human genome variation from population-scale sequencing in NATURE
  • 2011-07. Whole-genome sequencing identifies recurrent mutations in chronic lymphocytic leukaemia in NATURE
  • 2006-12. Differences in the evolutionary history of disease genes affected by dominant or recessive mutations in BMC GENOMICS
  • 2012-01. Exome sequencing identifies recurrent mutations of the splicing factor SF3B1 gene in chronic lymphocytic leukemia in NATURE GENETICS
  • 2008-10-23. Comprehensive genomic characterization defines human glioblastoma genes and core pathways in NATURE
  • 2000-05. Gene Ontology: tool for the unification of biology in NATURE GENETICS
  • 2010-10. Advances in understanding cancer genomes through second-generation sequencing in NATURE REVIEWS GENETICS
  • 2011-12. Deep sequencing of gastric carcinoma reveals somatic mutations relevant to personalized medicine in JOURNAL OF TRANSLATIONAL MEDICINE
  • 2008-10-23. Somatic mutations affect key pathways in lung adenocarcinoma in NATURE
  • 2009-07. Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm in NATURE PROTOCOLS
  • 2012-02. Driver mutations in histone H3.3 and chromatin remodelling genes in paediatric glioblastoma in NATURE
  • 2011-06-29. Integrated genomic analyses of ovarian carcinoma in NATURE
  • 2004-03. A census of human cancer genes in NATURE REVIEWS CANCER
  • 2012-06. The landscape of cancer genes and mutational processes in breast cancer in NATURE
  • 2010-04. A method and server for predicting damaging missense mutations in NATURE METHODS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/gm390

    DOI

    http://dx.doi.org/10.1186/gm390

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1004946181

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/23181723


    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/2008/1112", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Oncology and Carcinogenesis", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Medical and Health Sciences", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Institut Hospital del Mar d'Investigacions M\u00e8diques", 
              "id": "https://www.grid.ac/institutes/grid.20522.37", 
              "name": [
                "Research Programme on Biomedical Informatics - GRIB. Universitat Pompeu Fabra - UPF, Hospital del Mar Medical Research Institute - IMIM. Parc de Recerca Biom\u00e8dica de Barcelona (PRBB). Dr. Aiguader, 88, E-08003, Barcelona, Spain"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Gonzalez-Perez", 
            "givenName": "Abel", 
            "id": "sg:person.01250203315.54", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01250203315.54"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Institut Hospital del Mar d'Investigacions M\u00e8diques", 
              "id": "https://www.grid.ac/institutes/grid.20522.37", 
              "name": [
                "Research Programme on Biomedical Informatics - GRIB. Universitat Pompeu Fabra - UPF, Hospital del Mar Medical Research Institute - IMIM. Parc de Recerca Biom\u00e8dica de Barcelona (PRBB). Dr. Aiguader, 88, E-08003, Barcelona, Spain"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Deu-Pons", 
            "givenName": "Jordi", 
            "id": "sg:person.0616626645.06", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0616626645.06"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Instituci\u00f3 Catalana de Recerca i Estudis Avan\u00e7ats", 
              "id": "https://www.grid.ac/institutes/grid.425902.8", 
              "name": [
                "Research Programme on Biomedical Informatics - GRIB. Universitat Pompeu Fabra - UPF, Hospital del Mar Medical Research Institute - IMIM. Parc de Recerca Biom\u00e8dica de Barcelona (PRBB). Dr. Aiguader, 88, E-08003, Barcelona, Spain", 
                "Instituci\u00f3 Catalana de Recerca i Estudis Avan\u00e7ats (ICREA). Passeig Llu\u00eds Companys, 23, E-08010, Barcelona, Spain"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Lopez-Bigas", 
            "givenName": "Nuria", 
            "id": "sg:person.01232662277.25", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01232662277.25"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1002/humu.21445", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000630026"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature10166", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000736346", 
              "https://doi.org/10.1038/nature10166"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1133427", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000786924"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkg509", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002198958"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1479-5876-9-119", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003297095", 
              "https://doi.org/10.1186/1479-5876-9-119"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/gr.125567.111", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003952222"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/humu.22102", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005068015"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/leu.2011.326", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006336284", 
              "https://doi.org/10.1038/leu.2011.326"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1164368", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006710792"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkq963", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007075476"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth0410-248", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007489634", 
              "https://doi.org/10.1038/nmeth0410-248"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth0410-248", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007489634", 
              "https://doi.org/10.1038/nmeth0410-248"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2164-11-293", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007878504", 
              "https://doi.org/10.1186/1471-2164-11-293"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature10113", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008698030", 
              "https://doi.org/10.1038/nature10113"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2105-7-166", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008763878", 
              "https://doi.org/10.1186/1471-2105-7-166"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btr357", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009506595"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkr407", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009603644"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature08987", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010562574", 
              "https://doi.org/10.1038/nature08987"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature08987", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010562574", 
              "https://doi.org/10.1038/nature08987"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature09534", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010608717", 
              "https://doi.org/10.1038/nature09534"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature09534", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010608717", 
              "https://doi.org/10.1038/nature09534"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/gr.6431107", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013197352"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1111/j.1755-148x.2012.00976.x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013493963"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nprot.2009.86", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015642657", 
              "https://doi.org/10.1038/nprot.2009.86"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkp985", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016317136"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrg2841", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017741162", 
              "https://doi.org/10.1038/nrg2841"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrg2841", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017741162", 
              "https://doi.org/10.1038/nrg2841"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/bti781", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019878224"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/bti781", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019878224"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/database/bar026", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020300753"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrc1299", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022731034", 
              "https://doi.org/10.1038/nrc1299"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrc1299", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022731034", 
              "https://doi.org/10.1038/nrc1299"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.cell.2011.02.013", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023540354"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1158/0008-5472.can-09-1133", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024091199"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gki033", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1032298109"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature11017", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034041413", 
              "https://doi.org/10.1038/nature11017"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ajhg.2011.03.004", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035003425"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1182/blood-2011-08-373159", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035649645"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2164-7-165", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036234801", 
              "https://doi.org/10.1186/1471-2164-7-165"
            ], 
            "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": "https://doi.org/10.1093/nar/gkn828", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038202091"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature07385", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039570773", 
              "https://doi.org/10.1038/nature07385"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature10833", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039575824", 
              "https://doi.org/10.1038/nature10833"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btl348", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040498786"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.cmpb.2006.12.003", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043028922"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkf493", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043756780"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/75556", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044135237", 
              "https://doi.org/10.1038/75556"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/75556", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044135237", 
              "https://doi.org/10.1038/75556"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature07423", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044282578", 
              "https://doi.org/10.1038/nature07423"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkm405", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045071872"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng.1032", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046870423", 
              "https://doi.org/10.1038/ng.1032"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btq330", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047117020"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1164382", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1048029720"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.cell.2011.12.013", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050797629"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.4161/cbt.10.6.12537", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052307007"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btm551", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1053363845"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1145720", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1053548183"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1077638796", 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2012-11", 
        "datePublishedReg": "2012-11-01", 
        "description": "High-throughput prioritization of cancer-causing mutations (drivers) is a key challenge of cancer genome projects, due to the number of somatic variants detected in tumors. One important step in this task is to assess the functional impact of tumor somatic mutations. A number of computational methods have been employed for that purpose, although most were originally developed to distinguish disease-related nonsynonymous single nucleotide variants (nsSNVs) from polymorphisms. Our new method, transformed Functional Impact score for Cancer (transFIC), improves the assessment of the functional impact of tumor nsSNVs by taking into account the baseline tolerance of genes to functional variants. ", 
        "genre": "research_article", 
        "id": "sg:pub.10.1186/gm390", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": true, 
        "isPartOf": [
          {
            "id": "sg:journal.1040124", 
            "issn": [
              "1756-994X"
            ], 
            "name": "Genome Medicine", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "11", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "4"
          }
        ], 
        "name": "Improving the prediction of the functional impact of cancer mutations by baseline tolerance transformation", 
        "pagination": "89", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "1791e960c56657a6e361836bef7e95ab346b78074b975a61d19fb41698efb15d"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "23181723"
            ]
          }, 
          {
            "name": "nlm_unique_id", 
            "type": "PropertyValue", 
            "value": [
              "101475844"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1186/gm390"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1004946181"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1186/gm390", 
          "https://app.dimensions.ai/details/publication/pub.1004946181"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-10T15:06", 
        "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_8663_00000536.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "http://link.springer.com/10.1186%2Fgm390"
      }
    ]
     

    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.10.1186/gm390'

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

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/gm390'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/gm390'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/gm390'


     

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

    257 TRIPLES      21 PREDICATES      80 URIs      21 LITERALS      9 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1186/gm390 schema:about anzsrc-for:11
    2 anzsrc-for:1112
    3 schema:author N10f428eaf5044298a1ef2031dd82d22d
    4 schema:citation sg:pub.10.1038/75556
    5 sg:pub.10.1038/leu.2011.326
    6 sg:pub.10.1038/nature07385
    7 sg:pub.10.1038/nature07423
    8 sg:pub.10.1038/nature08987
    9 sg:pub.10.1038/nature09534
    10 sg:pub.10.1038/nature10113
    11 sg:pub.10.1038/nature10166
    12 sg:pub.10.1038/nature10833
    13 sg:pub.10.1038/nature11017
    14 sg:pub.10.1038/ng.1032
    15 sg:pub.10.1038/nmeth0410-248
    16 sg:pub.10.1038/nprot.2009.86
    17 sg:pub.10.1038/nrc1299
    18 sg:pub.10.1038/nrg2841
    19 sg:pub.10.1186/1471-2105-7-166
    20 sg:pub.10.1186/1471-2164-11-293
    21 sg:pub.10.1186/1471-2164-7-165
    22 sg:pub.10.1186/1479-5876-9-119
    23 https://app.dimensions.ai/details/publication/pub.1077638796
    24 https://doi.org/10.1002/humu.21445
    25 https://doi.org/10.1002/humu.22102
    26 https://doi.org/10.1016/j.ajhg.2011.03.004
    27 https://doi.org/10.1016/j.cell.2011.02.013
    28 https://doi.org/10.1016/j.cell.2011.12.013
    29 https://doi.org/10.1016/j.cmpb.2006.12.003
    30 https://doi.org/10.1073/pnas.0506580102
    31 https://doi.org/10.1093/bioinformatics/bti781
    32 https://doi.org/10.1093/bioinformatics/btl348
    33 https://doi.org/10.1093/bioinformatics/btm551
    34 https://doi.org/10.1093/bioinformatics/btq330
    35 https://doi.org/10.1093/bioinformatics/btr357
    36 https://doi.org/10.1093/database/bar026
    37 https://doi.org/10.1093/nar/gkf493
    38 https://doi.org/10.1093/nar/gkg509
    39 https://doi.org/10.1093/nar/gki033
    40 https://doi.org/10.1093/nar/gkm405
    41 https://doi.org/10.1093/nar/gkn828
    42 https://doi.org/10.1093/nar/gkp985
    43 https://doi.org/10.1093/nar/gkq963
    44 https://doi.org/10.1093/nar/gkr407
    45 https://doi.org/10.1101/gr.125567.111
    46 https://doi.org/10.1101/gr.6431107
    47 https://doi.org/10.1111/j.1755-148x.2012.00976.x
    48 https://doi.org/10.1126/science.1133427
    49 https://doi.org/10.1126/science.1145720
    50 https://doi.org/10.1126/science.1164368
    51 https://doi.org/10.1126/science.1164382
    52 https://doi.org/10.1158/0008-5472.can-09-1133
    53 https://doi.org/10.1182/blood-2011-08-373159
    54 https://doi.org/10.4161/cbt.10.6.12537
    55 schema:datePublished 2012-11
    56 schema:datePublishedReg 2012-11-01
    57 schema:description High-throughput prioritization of cancer-causing mutations (drivers) is a key challenge of cancer genome projects, due to the number of somatic variants detected in tumors. One important step in this task is to assess the functional impact of tumor somatic mutations. A number of computational methods have been employed for that purpose, although most were originally developed to distinguish disease-related nonsynonymous single nucleotide variants (nsSNVs) from polymorphisms. Our new method, transformed Functional Impact score for Cancer (transFIC), improves the assessment of the functional impact of tumor nsSNVs by taking into account the baseline tolerance of genes to functional variants.
    58 schema:genre research_article
    59 schema:inLanguage en
    60 schema:isAccessibleForFree true
    61 schema:isPartOf N2d71aaa8f02f46d6b6be7761c1d3cfcc
    62 Nbdafbf055c6c4a66901b0394e1d8507c
    63 sg:journal.1040124
    64 schema:name Improving the prediction of the functional impact of cancer mutations by baseline tolerance transformation
    65 schema:pagination 89
    66 schema:productId N6160a78f6ad4462c8e7ec9ebe87a4c90
    67 N61cdfac1a8074f4a93773f9a1910590a
    68 N970b65ab2c5b4ee7ad99f7e2dc35c17e
    69 Na8e4e5020989477dadc0dca828f8cb0e
    70 Nd6eaf8f440c748d7aa098e9544138557
    71 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004946181
    72 https://doi.org/10.1186/gm390
    73 schema:sdDatePublished 2019-04-10T15:06
    74 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    75 schema:sdPublisher N145dccbb411f4402b026d0cf7c5e1fa5
    76 schema:url http://link.springer.com/10.1186%2Fgm390
    77 sgo:license sg:explorer/license/
    78 sgo:sdDataset articles
    79 rdf:type schema:ScholarlyArticle
    80 N10f428eaf5044298a1ef2031dd82d22d rdf:first sg:person.01250203315.54
    81 rdf:rest N5e2402c8143d4e45aa8f846569a7b20e
    82 N145dccbb411f4402b026d0cf7c5e1fa5 schema:name Springer Nature - SN SciGraph project
    83 rdf:type schema:Organization
    84 N2d71aaa8f02f46d6b6be7761c1d3cfcc schema:issueNumber 11
    85 rdf:type schema:PublicationIssue
    86 N5e2402c8143d4e45aa8f846569a7b20e rdf:first sg:person.0616626645.06
    87 rdf:rest Nb5c482bbe7da4028a504f9932ede1572
    88 N6160a78f6ad4462c8e7ec9ebe87a4c90 schema:name nlm_unique_id
    89 schema:value 101475844
    90 rdf:type schema:PropertyValue
    91 N61cdfac1a8074f4a93773f9a1910590a schema:name readcube_id
    92 schema:value 1791e960c56657a6e361836bef7e95ab346b78074b975a61d19fb41698efb15d
    93 rdf:type schema:PropertyValue
    94 N970b65ab2c5b4ee7ad99f7e2dc35c17e schema:name doi
    95 schema:value 10.1186/gm390
    96 rdf:type schema:PropertyValue
    97 Na8e4e5020989477dadc0dca828f8cb0e schema:name dimensions_id
    98 schema:value pub.1004946181
    99 rdf:type schema:PropertyValue
    100 Nb5c482bbe7da4028a504f9932ede1572 rdf:first sg:person.01232662277.25
    101 rdf:rest rdf:nil
    102 Nbdafbf055c6c4a66901b0394e1d8507c schema:volumeNumber 4
    103 rdf:type schema:PublicationVolume
    104 Nd6eaf8f440c748d7aa098e9544138557 schema:name pubmed_id
    105 schema:value 23181723
    106 rdf:type schema:PropertyValue
    107 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
    108 schema:name Medical and Health Sciences
    109 rdf:type schema:DefinedTerm
    110 anzsrc-for:1112 schema:inDefinedTermSet anzsrc-for:
    111 schema:name Oncology and Carcinogenesis
    112 rdf:type schema:DefinedTerm
    113 sg:journal.1040124 schema:issn 1756-994X
    114 schema:name Genome Medicine
    115 rdf:type schema:Periodical
    116 sg:person.01232662277.25 schema:affiliation https://www.grid.ac/institutes/grid.425902.8
    117 schema:familyName Lopez-Bigas
    118 schema:givenName Nuria
    119 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01232662277.25
    120 rdf:type schema:Person
    121 sg:person.01250203315.54 schema:affiliation https://www.grid.ac/institutes/grid.20522.37
    122 schema:familyName Gonzalez-Perez
    123 schema:givenName Abel
    124 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01250203315.54
    125 rdf:type schema:Person
    126 sg:person.0616626645.06 schema:affiliation https://www.grid.ac/institutes/grid.20522.37
    127 schema:familyName Deu-Pons
    128 schema:givenName Jordi
    129 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0616626645.06
    130 rdf:type schema:Person
    131 sg:pub.10.1038/75556 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044135237
    132 https://doi.org/10.1038/75556
    133 rdf:type schema:CreativeWork
    134 sg:pub.10.1038/leu.2011.326 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006336284
    135 https://doi.org/10.1038/leu.2011.326
    136 rdf:type schema:CreativeWork
    137 sg:pub.10.1038/nature07385 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039570773
    138 https://doi.org/10.1038/nature07385
    139 rdf:type schema:CreativeWork
    140 sg:pub.10.1038/nature07423 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044282578
    141 https://doi.org/10.1038/nature07423
    142 rdf:type schema:CreativeWork
    143 sg:pub.10.1038/nature08987 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010562574
    144 https://doi.org/10.1038/nature08987
    145 rdf:type schema:CreativeWork
    146 sg:pub.10.1038/nature09534 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010608717
    147 https://doi.org/10.1038/nature09534
    148 rdf:type schema:CreativeWork
    149 sg:pub.10.1038/nature10113 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008698030
    150 https://doi.org/10.1038/nature10113
    151 rdf:type schema:CreativeWork
    152 sg:pub.10.1038/nature10166 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000736346
    153 https://doi.org/10.1038/nature10166
    154 rdf:type schema:CreativeWork
    155 sg:pub.10.1038/nature10833 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039575824
    156 https://doi.org/10.1038/nature10833
    157 rdf:type schema:CreativeWork
    158 sg:pub.10.1038/nature11017 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034041413
    159 https://doi.org/10.1038/nature11017
    160 rdf:type schema:CreativeWork
    161 sg:pub.10.1038/ng.1032 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046870423
    162 https://doi.org/10.1038/ng.1032
    163 rdf:type schema:CreativeWork
    164 sg:pub.10.1038/nmeth0410-248 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007489634
    165 https://doi.org/10.1038/nmeth0410-248
    166 rdf:type schema:CreativeWork
    167 sg:pub.10.1038/nprot.2009.86 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015642657
    168 https://doi.org/10.1038/nprot.2009.86
    169 rdf:type schema:CreativeWork
    170 sg:pub.10.1038/nrc1299 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022731034
    171 https://doi.org/10.1038/nrc1299
    172 rdf:type schema:CreativeWork
    173 sg:pub.10.1038/nrg2841 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017741162
    174 https://doi.org/10.1038/nrg2841
    175 rdf:type schema:CreativeWork
    176 sg:pub.10.1186/1471-2105-7-166 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008763878
    177 https://doi.org/10.1186/1471-2105-7-166
    178 rdf:type schema:CreativeWork
    179 sg:pub.10.1186/1471-2164-11-293 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007878504
    180 https://doi.org/10.1186/1471-2164-11-293
    181 rdf:type schema:CreativeWork
    182 sg:pub.10.1186/1471-2164-7-165 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036234801
    183 https://doi.org/10.1186/1471-2164-7-165
    184 rdf:type schema:CreativeWork
    185 sg:pub.10.1186/1479-5876-9-119 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003297095
    186 https://doi.org/10.1186/1479-5876-9-119
    187 rdf:type schema:CreativeWork
    188 https://app.dimensions.ai/details/publication/pub.1077638796 schema:CreativeWork
    189 https://doi.org/10.1002/humu.21445 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000630026
    190 rdf:type schema:CreativeWork
    191 https://doi.org/10.1002/humu.22102 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005068015
    192 rdf:type schema:CreativeWork
    193 https://doi.org/10.1016/j.ajhg.2011.03.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035003425
    194 rdf:type schema:CreativeWork
    195 https://doi.org/10.1016/j.cell.2011.02.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023540354
    196 rdf:type schema:CreativeWork
    197 https://doi.org/10.1016/j.cell.2011.12.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050797629
    198 rdf:type schema:CreativeWork
    199 https://doi.org/10.1016/j.cmpb.2006.12.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043028922
    200 rdf:type schema:CreativeWork
    201 https://doi.org/10.1073/pnas.0506580102 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037705714
    202 rdf:type schema:CreativeWork
    203 https://doi.org/10.1093/bioinformatics/bti781 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019878224
    204 rdf:type schema:CreativeWork
    205 https://doi.org/10.1093/bioinformatics/btl348 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040498786
    206 rdf:type schema:CreativeWork
    207 https://doi.org/10.1093/bioinformatics/btm551 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053363845
    208 rdf:type schema:CreativeWork
    209 https://doi.org/10.1093/bioinformatics/btq330 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047117020
    210 rdf:type schema:CreativeWork
    211 https://doi.org/10.1093/bioinformatics/btr357 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009506595
    212 rdf:type schema:CreativeWork
    213 https://doi.org/10.1093/database/bar026 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020300753
    214 rdf:type schema:CreativeWork
    215 https://doi.org/10.1093/nar/gkf493 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043756780
    216 rdf:type schema:CreativeWork
    217 https://doi.org/10.1093/nar/gkg509 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002198958
    218 rdf:type schema:CreativeWork
    219 https://doi.org/10.1093/nar/gki033 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032298109
    220 rdf:type schema:CreativeWork
    221 https://doi.org/10.1093/nar/gkm405 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045071872
    222 rdf:type schema:CreativeWork
    223 https://doi.org/10.1093/nar/gkn828 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038202091
    224 rdf:type schema:CreativeWork
    225 https://doi.org/10.1093/nar/gkp985 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016317136
    226 rdf:type schema:CreativeWork
    227 https://doi.org/10.1093/nar/gkq963 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007075476
    228 rdf:type schema:CreativeWork
    229 https://doi.org/10.1093/nar/gkr407 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009603644
    230 rdf:type schema:CreativeWork
    231 https://doi.org/10.1101/gr.125567.111 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003952222
    232 rdf:type schema:CreativeWork
    233 https://doi.org/10.1101/gr.6431107 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013197352
    234 rdf:type schema:CreativeWork
    235 https://doi.org/10.1111/j.1755-148x.2012.00976.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1013493963
    236 rdf:type schema:CreativeWork
    237 https://doi.org/10.1126/science.1133427 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000786924
    238 rdf:type schema:CreativeWork
    239 https://doi.org/10.1126/science.1145720 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053548183
    240 rdf:type schema:CreativeWork
    241 https://doi.org/10.1126/science.1164368 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006710792
    242 rdf:type schema:CreativeWork
    243 https://doi.org/10.1126/science.1164382 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048029720
    244 rdf:type schema:CreativeWork
    245 https://doi.org/10.1158/0008-5472.can-09-1133 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024091199
    246 rdf:type schema:CreativeWork
    247 https://doi.org/10.1182/blood-2011-08-373159 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035649645
    248 rdf:type schema:CreativeWork
    249 https://doi.org/10.4161/cbt.10.6.12537 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052307007
    250 rdf:type schema:CreativeWork
    251 https://www.grid.ac/institutes/grid.20522.37 schema:alternateName Institut Hospital del Mar d'Investigacions Mèdiques
    252 schema:name Research Programme on Biomedical Informatics - GRIB. Universitat Pompeu Fabra - UPF, Hospital del Mar Medical Research Institute - IMIM. Parc de Recerca Biomèdica de Barcelona (PRBB). Dr. Aiguader, 88, E-08003, Barcelona, Spain
    253 rdf:type schema:Organization
    254 https://www.grid.ac/institutes/grid.425902.8 schema:alternateName Institució Catalana de Recerca i Estudis Avançats
    255 schema:name Institució Catalana de Recerca i Estudis Avançats (ICREA). Passeig Lluís Companys, 23, E-08010, Barcelona, Spain
    256 Research Programme on Biomedical Informatics - GRIB. Universitat Pompeu Fabra - UPF, Hospital del Mar Medical Research Institute - IMIM. Parc de Recerca Biomèdica de Barcelona (PRBB). Dr. Aiguader, 88, E-08003, Barcelona, Spain
    257 rdf:type schema:Organization
     




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


    ...