Please use this identifier to cite or link to this item: https://biore.bio.bg.ac.rs/handle/123456789/387
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dc.contributor.authorĐorđević, Markoen_US
dc.date.accessioned2019-07-01T20:01:10Z-
dc.date.available2019-07-01T20:01:10Z-
dc.date.issued2014-01-01-
dc.identifier.isbn9783885796299-
dc.identifier.issn1617-5468-
dc.identifier.urihttps://biore.bio.bg.ac.rs/handle/123456789/387-
dc.description.abstractPromoter prediction in bacteria is a classical bioinformatics problem, where available methods for regulatory element detection exhibit a very high number of false positives. We here argue that accurate transcription start site (TSS) prediction is a complex problem, where available methods for sequence motif discovery are not in itself well adopted for solving the problem. We here instead propose that the problem requires integration of quantitative understanding of transcription initiation with careful description of promoter sequence specificity. We review evidence for this viewpoint based on our recent work, and discuss a current progress on accurate TSS detection on the example of sigma70 transcription start sites in E. coli.en_US
dc.relation.ispartofLecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)en_US
dc.titleTowards accurate transcription start site prediction: A modelling approachen_US
dc.typeArticleen_US
dc.identifier.scopus2-s2.0-84919385181-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/84919385181-
item.cerifentitytypePublications-
item.openairetypeArticle-
item.fulltextWith Fulltext-
item.grantfulltextrestricted-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
crisitem.author.deptChair of General Physiology and Biophysics-
crisitem.author.orcid0000-0002-2903-3119-
Appears in Collections:Journal Article
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