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MSCAN: identification of functional clusters of transcription factor binding sites
KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
2004 (English)In: Nucleic Acids Research, ISSN 0305-1048, E-ISSN 1362-4962, Vol. 32, W195-W198 p.Article in journal (Refereed) Published
Abstract [en]

Identification of functional transcription factor binding sites in genomic sequences is notoriously difficult. The critical problem is the low specificity of predictions, which directly reflects the low target specificity of DNA binding proteins. To overcome the noise produced in predictions of individual binding sites, a new generation of algorithms achieves better predictive specificity by focusing on locally dense clusters of binding sites. MSCAN is a leading method for binding site cluster detection that determines the significance of observed sites while correcting for local compositional bias of sequences. The algorithm is highly flexible, applying any set of input binding models to the analysis of a user-specified sequence. From the user's perspective, a key feature of the system is that no reference data sets of regulatory sequences from co-regulated genes are required to train the algorithm. The output from MSCAN consists of an ordered list of sequence segments that contain potential regulatory modules. We have chosen the features in MSCAN such that sequence and matrix retrieval is highly facilitated, resulting in a web server that is intuitive to use. MSCAN is available at

Place, publisher, year, edition, pages
2004. Vol. 32, W195-W198 p.
Keyword [en]
target genes, profiles, modules
National Category
Computer and Information Science
URN: urn:nbn:se:kth:diva-23537DOI: 10.1093/nar/gkh387ISI: 000222273100041ScopusID: 2-s2.0-3242882572OAI: diva2:342235
QC 20100525 QC 20111103Available from: 2010-08-10 Created: 2010-08-10 Last updated: 2011-11-03Bibliographically approved

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Lagergren, Jens
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Numerical Analysis and Computer Science, NADA
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