Maximum likelihood estimation of weight matrices for targeted homology search
dc.contributor.author | Menzel, Peter | |
dc.contributor.author | Gorodkin, Jan | |
dc.contributor.author | Stadler, Peter F. | |
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 | 2019-02-20T09:48:30Z | |
dc.date.available | 2019-02-20T09:48:30Z | |
dc.date.issued | 2009 | |
dc.description.abstract | Genome annotation relies to a large extent on the recognition of homologs to already known genes. The starting point for such protocols is a collection of known sequences from one or more species, from which a model is constructed – either automatically or manually – that encodes the defining features of a single gene or a gene family. The quality of these models eventually determines the success rate of the homology search. We propose here a novel approach to model construction that not only captures the characteristic motifs of a gene, but are also adjusts the search pattern by including phylogenetic information. Computational tests demonstrate that this can lead to a substantial improvement of homology search models. | en |
dc.identifier.isbn | 978-3-88579-251-2 | |
dc.identifier.pissn | 1617-5468 | |
dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/20305 | |
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 | Maximum likelihood estimation of weight matrices for targeted homology search | en |
dc.type | Text/Conference Paper | |
gi.citation.endPage | 220 | |
gi.citation.publisherPlace | Bonn | |
gi.citation.startPage | 211 | |
gi.conference.date | 28th to 30th September 2009 | |
gi.conference.location | Halle-Wittenberg | |
gi.conference.sessiontitle | Regular Research Papers |
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