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dc.contributor.authorDeyneko, Igor V
dc.contributor.authorWeiss, Siegfried
dc.contributor.authorLeschner, Sara
dc.date.accessioned2013-08-14T13:38:04Z
dc.date.available2013-08-14T13:38:04Z
dc.date.issued2012
dc.identifier.citationAn integrative computational approach to effectively guide experimental identification of regulatory elements in promoters. 2012, 13:202 BMC Bioinformaticsen_GB
dc.identifier.issn1471-2105
dc.identifier.pmid22897887
dc.identifier.doi10.1186/1471-2105-13-202
dc.identifier.urihttp://hdl.handle.net/10033/298245
dc.description.abstractTranscriptional activity of genes depends on many factors like DNA motifs, conformational characteristics of DNA, melting etc. and there are computational approaches for their identification. However, in real applications, the number of predicted, for example, DNA motifs may be considerably large. In cases when various computational programs are applied, systematic experimental knock out of each of the potential elements obviously becomes nonproductive. Hence, one needs an approach that is able to integrate many heterogeneous computational methods and upon that suggest selected regulatory elements for experimental verification.
dc.language.isoenen
dc.rightsArchived with thanks to BMC bioinformaticsen_GB
dc.subject.meshAlgorithmsen_GB
dc.subject.meshComputational Biologyen_GB
dc.subject.meshGene Expressionen_GB
dc.subject.meshNeoplasmsen_GB
dc.subject.meshNucleotide Motifsen_GB
dc.subject.meshPromoter Regions, Geneticen_GB
dc.subject.meshSalmonellaen_GB
dc.subject.meshSequence Analysis, DNAen_GB
dc.titleAn integrative computational approach to effectively guide experimental identification of regulatory elements in promoters.en
dc.typeArticleen
dc.contributor.departmentMolecular Immunology, Helmholtz Centre for Infection Research, Inhoffenstr, 7, 38124 Braunschweig, Germany. Igor.Deyneko@helmholtz-hzi.deen_GB
dc.identifier.journalBMC bioinformaticsen_GB
refterms.dateFOA2018-06-13T15:51:15Z
html.description.abstractTranscriptional activity of genes depends on many factors like DNA motifs, conformational characteristics of DNA, melting etc. and there are computational approaches for their identification. However, in real applications, the number of predicted, for example, DNA motifs may be considerably large. In cases when various computational programs are applied, systematic experimental knock out of each of the potential elements obviously becomes nonproductive. Hence, one needs an approach that is able to integrate many heterogeneous computational methods and upon that suggest selected regulatory elements for experimental verification.


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