Informational Requirements for Transcriptional Regulation

Simple item page
dc.contributor.authorO'Neill, Patrick K.
dc.contributor.authorForder, Robert
dc.contributor.authorErill, Ivan
dc.date.accessioned2018-10-15T14:27:53Z
dc.date.available2018-10-15T14:27:53Z
dc.date.issued2014-05-01
dc.description.abstractTranscription factors (TFs) regulate transcription by binding to specific sites in promoter regions. Information theory provides a useful mathematical framework to analyze the binding motifs associated with TFs but imposes several assumptions that limit their applicability to specific regulatory scenarios. Explicit simulations of the co-evolution of TFs and their binding motifs allow the study of the evolution of regulatory networks with a high degree of realism. In this work we analyze the impact of differential regulatory demands on the information content of TF-binding motifs by means of evolutionary simulations. We generalize a predictive index based on information theory, and we validate its applicability to regulatory scenarios in which the TF binds significantly to the genomic background. Our results show a logarithmic dependence of the evolved information content on the occupancy of target sites and indicate that TFs may actively exploit pseudo-sites to modulate their occupancy of target sites. In regulatory networks with differentially regulated targets, we observe that information content in TF-binding motifs is dictated primarily by the fraction of total probability mass that the TF assigns to its target sites, and we provide a predictive index to estimate the amount of information associated with arbitrarily complex regulatory systems. We observe that complex regulatory patterns can exert additional demands on evolved information content, but, given a total occupancy for target sites, we do not find conclusive evidence that this effect is because of the range of required binding affinities.en_US
dc.description.urihttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4010175/en_US
dc.format.extent12 pagesen_US
dc.genreJournal Articleen_US
dc.identifierdoi:10.13016/M2222R94S
dc.identifier.citationPatrick K. O'Neill, Robert Forder, Ivan Erill, Informational Requirements for Transcriptional Regulation, Journal of Computational Biology Volume 21, Number 5, 2014 # Mary Ann Liebert, Inc. Pp. 373–384 DOI: 10.1089/cmb.2014.0032en_US
dc.identifier.uriDOI: 10.1089/cmb.2014.0032
dc.identifier.urihttp://hdl.handle.net/11603/11563
dc.language.isoen_USen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Biological Sciences Department Collection
dc.relation.ispartofUMBC Mathematics and Statistics Department
dc.relation.ispartofUMBC Faculty Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.subjectBinding sitesen_US
dc.subjectevolutionen_US
dc.subjectEvolutionary simulationen_US
dc.subjectIn silico evolutionen_US
dc.subjectInformation contenten_US
dc.subjectRegulationen_US
dc.subjectTranscription factoren_US
dc.subjectTranscription networksen_US
dc.titleInformational Requirements for Transcriptional Regulationen_US
dc.typeTexten_US

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
cmb.2014.0032.pdf
Size:
702.28 KB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.68 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

UMBC Biological Sciences Department
UMBC Faculty Collection
UMBC Mathematics and Statistics Department