Identification of cancer and cell-cycle genes with protein interactions and literature mining
| dc.contributor.author | Royer, Loic | |
| dc.contributor.author | Plake, Conrad | |
| dc.contributor.author | Schroeder, Michael | |
| dc.contributor.editor | Grosse, Ivo | |
| dc.contributor.editor | Neumann, Steffen | |
| dc.contributor.editor | Posch, Stefan | |
| dc.contributor.editor | Schreiber, Falk | |
| dc.contributor.editor | Stadler, Peter | |
| dc.date.accessioned | 2019-02-20T09:48:31Z | |
| dc.date.available | 2019-02-20T09:48:31Z | |
| dc.date.issued | 2009 | |
| dc.description.abstract | Gene prioritization based on background knowledge mined from literature has become an important method for the analysis of results from high-throughput experimental assays such as gene expression microarrays, RNAi screens and genomewide association studies. We apply our gene mention identifier, which achieved the best result of over 80% in the BioCreative II text-mining challenge [HPR+08], and show how text-mined associations can be complemented using guilt-by-association on high confidence protein interaction networks. First, we predict hand-curated gene-disease relationships in the OMIM database, Entrez Gene summaries and GeneRIFs with 37% success rate. Second, we confirm 24% of novel cell-cycle genes identified in a recent RNAi screen [KPH+07] by using text-mining and high confidence protein interactions. Moreover, we show how 71% of GOA cell-cycle annotations can be automatically recovered. Third, we devise a method to rank genes based on novelty, increasing interest, impact, and popularity. | en |
| dc.identifier.isbn | 978-3-88579-251-2 | |
| dc.identifier.pissn | 1617-5468 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/20312 | |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik e.V. | |
| dc.relation.ispartof | German conference on bioinformatics 2009 | |
| dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-157 | |
| dc.title | Identification of cancer and cell-cycle genes with protein interactions and literature mining | en |
| dc.type | Text/Conference Paper | |
| gi.citation.endPage | 92 | |
| gi.citation.publisherPlace | Bonn | |
| gi.citation.startPage | 81 | |
| gi.conference.date | 28th to 30th September 2009 | |
| gi.conference.location | Halle-Wittenberg | |
| gi.conference.sessiontitle | Regular Research Papers |
Dateien
Originalbündel
1 - 1 von 1