MatrixCatch--a novel tool for the recognition of composite regulatory elements in promoters.

Deyneko, Igor V; Kel, Alexander E; Kel-Margoulis, Olga V; Deineko, Elena V; Wingender, Edgar; Weiss, Siegfried

dc.contributor.author	Deyneko, Igor V
dc.contributor.author	Kel, Alexander E
dc.contributor.author	Kel-Margoulis, Olga V
dc.contributor.author	Deineko, Elena V
dc.contributor.author	Wingender, Edgar
dc.contributor.author	Weiss, Siegfried
dc.date.accessioned	2013-10-08T10:40:39Z	en
dc.date.available	2013-10-08T10:40:39Z	en
dc.date.issued	2013	en
dc.identifier.citation	MatrixCatch--a novel tool for the recognition of composite regulatory elements in promoters. 2013, 14:241 BMC Bioinformatics	en
dc.identifier.issn	1471-2105	en
dc.identifier.pmid	23924163	en
dc.identifier.doi	10.1186/1471-2105-14-241	en
dc.identifier.uri	http://hdl.handle.net/10033/302967	en
dc.description.abstract	Accurate recognition of regulatory elements in promoters is an essential prerequisite for understanding the mechanisms of gene regulation at the level of transcription. Composite regulatory elements represent a particular type of such transcriptional regulatory elements consisting of pairs of individual DNA motifs. In contrast to the present approach, most available recognition techniques are based purely on statistical evaluation of the occurrence of single motifs. Such methods are limited in application, since the accuracy of recognition is greatly dependent on the size and quality of the sequence dataset. Methods that exploit available knowledge and have broad applicability are evidently needed.
dc.language.iso	en	en
dc.rights	Archived with thanks to BMC bioinformatics	en
dc.title	MatrixCatch--a novel tool for the recognition of composite regulatory elements in promoters.	en
dc.type	Article	en
dc.contributor.department	Department of Molecular Immunology, Helmholtz Centre for Infection Research, Braunschweig, Germany. Igor.Deyneko@helmholtz-hzi.de	en
dc.identifier.journal	BMC bioinformatics	en
refterms.dateFOA	2018-06-12T22:05:54Z
html.description.abstract	Accurate recognition of regulatory elements in promoters is an essential prerequisite for understanding the mechanisms of gene regulation at the level of transcription. Composite regulatory elements represent a particular type of such transcriptional regulatory elements consisting of pairs of individual DNA motifs. In contrast to the present approach, most available recognition techniques are based purely on statistical evaluation of the occurrence of single motifs. Such methods are limited in application, since the accuracy of recognition is greatly dependent on the size and quality of the sequence dataset. Methods that exploit available knowledge and have broad applicability are evidently needed.