Predicting miRNA targets utilizing an extended profile HMM
dc.contributor.author | Grau, Jan | |
dc.contributor.author | Arend, Daniel | |
dc.contributor.author | Grosse, Ivo | |
dc.contributor.author | Hatzigeorgiou, Artemis G. | |
dc.contributor.author | Keilwagen, Jens | |
dc.contributor.author | Maragkakis, Manolis | |
dc.contributor.author | Weinholdt, Claus | |
dc.contributor.author | Posch, Stefan | |
dc.contributor.editor | Schomburg, Dietmar | |
dc.contributor.editor | Grote, Andreas | |
dc.date.accessioned | 2019-01-17T10:57:30Z | |
dc.date.available | 2019-01-17T10:57:30Z | |
dc.date.issued | 2010 | |
dc.description.abstract | The regulation of many cellular processes is influenced by miRNAs, and bioinformatics approaches for predicting miRNA targets evolve rapidly. Here, we propose conditional profile HMMs that learn rules of miRNA-target site interaction automatically from data. We demonstrate that conditional profile HMMs detect the rules implemented into existing approaches from their predictions. And we show that a simple UTR model utilizing conditional profile HMMs predicts target genes of miR- NAs with a precision that is competitive compared to leading approaches, although it does not exploit cross-species conservation. | en |
dc.identifier.isbn | 978-3-88579-267-3 | |
dc.identifier.pissn | 1617-5468 | |
dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/19675 | |
dc.language.iso | en | |
dc.publisher | Gesellschaft für Informatik e.V. | |
dc.relation.ispartof | German Conference on Bioinformatics 2010 | |
dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-173 | |
dc.title | Predicting miRNA targets utilizing an extended profile HMM | en |
dc.type | Text/Conference Paper | |
gi.citation.endPage | 91 | |
gi.citation.publisherPlace | Bonn | |
gi.citation.startPage | 81 | |
gi.conference.date | September 20-22, 2010 | |
gi.conference.location | Braunschweig | |
gi.conference.sessiontitle | Regular Research Papers |
Dateien
Originalbündel
1 - 1 von 1