Application of Hidden Markov Models for Identification of Short Protein Repeats

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DC Field	Value	Language
dc.contributor.author	Bongardt, Friedhelm	de
dc.contributor.author	Urfer, Wolfgang	de
dc.contributor.author	Vetter, Ingrid	de
dc.date.accessioned	2004-12-06T18:50:26Z	-
dc.date.available	2004-12-06T18:50:26Z	-
dc.date.issued	2002	de
dc.identifier.uri	http://hdl.handle.net/2003/5246	-
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-15135	-
dc.description.abstract	In this paper, hidden Markov models (HMMs) are discussed in the context of molecular biological sequence analysis. The statistics relevant in the HMM approach are described in detail. An HMM based method is used to analyze two proteins that contain short protein repeats (SPRs). As a benchmark, a state-of-the-art program for the detection of SPRs is also used for both proteins. Finally, an outlook for combination possibilities of HMMs with phylogenetic approaches is given.	en
dc.format.extent	158957 bytes	-
dc.format.extent	402624 bytes	-
dc.format.mimetype	application/pdf	-
dc.format.mimetype	application/postscript	-
dc.language.iso	en	de
dc.publisher	Universitätsbibliothek Dortmund	de
dc.subject	hidden Markov models	en
dc.subject	short protein repeats	en
dc.subject.ddc	310	de
dc.title	Application of Hidden Markov Models for Identification of Short Protein Repeats	en
dc.type	Text	de
dc.type.publicationtype	report	en
dcterms.accessRights	open access	-
Appears in Collections:	Sonderforschungsbereich (SFB) 475

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