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Maximum likelihood estimation of weight matrices for targeted homology search

dc.contributor.authorMenzel, Peter
dc.contributor.authorGorodkin, Jan
dc.contributor.authorStadler, Peter F.
dc.contributor.editorGrosse, Ivo
dc.contributor.editorNeumann, Steffen
dc.contributor.editorPosch, Stefan
dc.contributor.editorSchreiber, Falk
dc.contributor.editorStadler, Peter
dc.date.accessioned2019-02-20T09:48:30Z
dc.date.available2019-02-20T09:48:30Z
dc.date.issued2009
dc.description.abstractGenome 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.isbn978-3-88579-251-2
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/20305
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofGerman conference on bioinformatics 2009
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-157
dc.titleMaximum likelihood estimation of weight matrices for targeted homology searchen
dc.typeText/Conference Paper
gi.citation.endPage220
gi.citation.publisherPlaceBonn
gi.citation.startPage211
gi.conference.date28th to 30th September 2009
gi.conference.locationHalle-Wittenberg
gi.conference.sessiontitleRegular Research Papers

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