Detection of gene communities in multi-networks reveals cancer drivers

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Cantini, L.
dc.contributor.author Medico, E.
dc.contributor.author Fortunato, Santo
dc.contributor.author Caselle, M.
dc.date.accessioned 2017-05-11T09:08:28Z
dc.date.available 2017-05-11T09:08:28Z
dc.date.issued 2015
dc.identifier.citation Cantini , L , Medico , E , Fortunato , S & Caselle , M 2015 , ' Detection of gene communities in multi-networks reveals cancer drivers ' SCIENTIFIC REPORTS , vol 5 , 17386 , pp. 1-10 . DOI: 10.1038/srep17386 en
dc.identifier.issn 2045-2322
dc.identifier.other PURE UUID: d31b5e30-15ee-471a-86b7-b3238aa1839f
dc.identifier.other PURE ITEMURL: https://research.aalto.fi/en/publications/detection-of-gene-communities-in-multinetworks-reveals-cancer-drivers(d31b5e30-15ee-471a-86b7-b3238aa1839f).html
dc.identifier.other PURE FILEURL: https://research.aalto.fi/files/12904726/srep17386.pdf
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/25877
dc.description VK: Fortunato, S.
dc.description.abstract We propose a new multi-network-based strategy to integrate different layers of genomic information and use them in a coordinate way to identify driving cancer genes. The multi-networks that we consider combine transcription factor co-targeting, microRNA co-targeting, protein-protein interaction and gene co-expression networks. The rationale behind this choice is that gene co-expression and protein-protein interactions require a tight coregulation of the partners and that such a fine tuned regulation can be obtained only combining both the transcriptional and post-transcriptional layers of regulation. To extract the relevant biological information from the multi-network we studied its partition into communities. To this end we applied a consensus clustering algorithm based on state of art community detection methods. Even if our procedure is valid in principle for any pathology in this work we concentrate on gastric, lung, pancreas and colorectal cancer and identified from the enrichment analysis of the multi-network communities a set of candidate driver cancer genes. Some of them were already known oncogenes while a few are new. The combination of the different layers of information allowed us to extract from the multi-network indications on the regulatory pattern and functional role of both the already known and the new candidate driver genes. en
dc.format.extent 1-10
dc.format.mimetype application/pdf
dc.language.iso en en
dc.relation.ispartofseries SCIENTIFIC REPORTS en
dc.relation.ispartofseries Volume 5 en
dc.rights openAccess en
dc.title Detection of gene communities in multi-networks reveals cancer drivers en
dc.type A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä fi
dc.description.version Peer reviewed en
dc.contributor.department Department of Computer Science en
dc.identifier.urn URN:NBN:fi:aalto-201705114252
dc.identifier.doi 10.1038/srep17386
dc.type.version publishedVersion


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