dc.contributor.author | Mlecnik, Bernhard | |
dc.contributor.author | Sanchez-Cabo, Fatima | |
dc.contributor.author | Charoentong, Pornpimol | |
dc.contributor.author | Bindea, Gabriela | |
dc.contributor.author | Pagès, Franck | |
dc.contributor.author | Berger, Anne | |
dc.contributor.author | Galon, Jerome | |
dc.contributor.author | Trajanoski, Zlatko | |
dc.date.accessioned | 2019-09-25T08:01:36Z | |
dc.date.available | 2019-09-25T08:01:36Z | |
dc.date.issued | 2010-02 | |
dc.identifier.citation | BMC Genomics. 2010; 11 Suppl 1:S7 | es_ES |
dc.identifier.issn | 1471-2164 | es_ES |
dc.identifier.uri | http://hdl.handle.net/20.500.12105/8379 | |
dc.description.abstract | Cancer 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.sponsorship | This 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.iso | eng | es_ES |
dc.publisher | BioMed Central (BMC) | es_ES |
dc.type.hasVersion | VoR | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.subject.mesh | Biometry | es_ES |
dc.subject.mesh | Computational Biology | es_ES |
dc.subject.mesh | Humans | es_ES |
dc.subject.mesh | Neoplasms | es_ES |
dc.subject.mesh | Software Design | es_ES |
dc.subject.mesh | Survival Rate | es_ES |
dc.subject.mesh | Databases, Factual | es_ES |
dc.title | Data integration and exploration for the identification of molecular mechanisms in tumor-immune cells interaction | es_ES |
dc.type | journal article | es_ES |
dc.rights.license | Atribución 4.0 Internacional | * |
dc.identifier.pubmedID | 20158878 | es_ES |
dc.format.volume | 11 Suppl 1 | es_ES |
dc.format.number | Suppl 1 | es_ES |
dc.format.page | S7 | es_ES |
dc.identifier.doi | 10.1186/1471-2164-11-S1-S7 | es_ES |
dc.contributor.funder | Australian Ministry for Science and Research | |
dc.contributor.funder | Australian Science Fund | |
dc.contributor.funder | Fondation ARC pour la recherche sur le cancer | |
dc.contributor.funder | Unión Europea. Comisión Europea | |
dc.description.peerreviewed | Sí | es_ES |
dc.identifier.e-issn | 1471-2164 | es_ES |
dc.relation.publisherversion | https://doi.org/10.1186/1471-2164-11-S1-S7 | es_ES |
dc.identifier.journal | BMC genomics | es_ES |
dc.repisalud.orgCNIC | CNIC::Unidades técnicas::Genómica | es_ES |
dc.repisalud.institucion | CNIC | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/FP7/202230/EU | es_ES |
dc.rights.accessRights | open access | es_ES |