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dc.contributor.authorMlecnik, Bernhard
dc.contributor.authorSanchez-Cabo, Fatima 
dc.contributor.authorCharoentong, Pornpimol
dc.contributor.authorBindea, Gabriela
dc.contributor.authorPagès, Franck
dc.contributor.authorBerger, Anne
dc.contributor.authorGalon, Jerome
dc.contributor.authorTrajanoski, Zlatko
dc.date.accessioned2019-09-25T08:01:36Z
dc.date.available2019-09-25T08:01:36Z
dc.date.issued2010-02
dc.identifier.citationBMC Genomics. 2010; 11 Suppl 1:S7es_ES
dc.identifier.issn1471-2164es_ES
dc.identifier.urihttp://hdl.handle.net/20.500.12105/8379
dc.description.abstractCancer progression is a complex process involving host-tumor interactions by multiple molecular and cellular factors of the tumor microenvironment. Tumor cells that challenge immune activity may be vulnerable to immune destruction. To address this question we have directed major efforts towards data integration and developed and installed a database for cancer immunology with more than 1700 patients and associated clinical data and biomolecular data. Mining of the database revealed novel insights into the molecular mechanisms of tumor-immune cell interaction. In this paper we present the computational tools used to analyze integrated clinical and biomolecular data. Specifically, we describe a database for heterogeneous data types, the interfacing bioinformatics and statistical tools including clustering methods, survival analysis, as well as visualization methods. Additionally, we discuss generic issues relevant to the integration of clinical and biomolecular data, as well as recent developments in integrative data analyses including biomolecular network reconstruction and mathematical modeling.es_ES
dc.description.sponsorshipThis work was supported by the Austrian Ministry for Science and Research, GEN-AU Project Bioinformatics Integration Network (BIN), Austrian Science Fund (SFB Project Lipotoxicity), INSERM, the National Cancer Institute (INCa), Association pour la Recherche sur le Cancer (ARC), the Cancéropole Ile de France, Ville de Paris, and by the European Commission (FP7, Geninca Consortium, grant number 202230).es_ES
dc.language.isoenges_ES
dc.publisherBioMed Central (BMC) es_ES
dc.type.hasVersionVoRes_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subject.meshBiometry es_ES
dc.subject.meshComputational Biology es_ES
dc.subject.meshHumans es_ES
dc.subject.meshNeoplasms es_ES
dc.subject.meshSoftware Design es_ES
dc.subject.meshSurvival Rate es_ES
dc.subject.meshDatabases, Factual es_ES
dc.titleData integration and exploration for the identification of molecular mechanisms in tumor-immune cells interactiones_ES
dc.typejournal articlees_ES
dc.rights.licenseAtribución 4.0 Internacional*
dc.identifier.pubmedID20158878es_ES
dc.format.volume11 Suppl 1es_ES
dc.format.numberSuppl 1es_ES
dc.format.pageS7es_ES
dc.identifier.doi10.1186/1471-2164-11-S1-S7es_ES
dc.contributor.funderAustralian Ministry for Science and Research
dc.contributor.funderAustralian Science Fund
dc.contributor.funderFondation ARC pour la recherche sur le cancer 
dc.contributor.funderUnión Europea. Comisión Europea 
dc.description.peerreviewedes_ES
dc.identifier.e-issn1471-2164es_ES
dc.relation.publisherversionhttps://doi.org/10.1186/1471-2164-11-S1-S7es_ES
dc.identifier.journalBMC genomicses_ES
dc.repisalud.orgCNICCNIC::Unidades técnicas::Genómicaes_ES
dc.repisalud.institucionCNICes_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/FP7/202230/EUes_ES
dc.rights.accessRightsopen accesses_ES


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Atribución 4.0 Internacional
Este Item está sujeto a una licencia Creative Commons: Atribución 4.0 Internacional