The information coded in the yeast response elements accounts for most of the topological properties of its transcriptional regulation network.

The regulation of gene expression in a cell relies to a major extent on transcription factors, proteins which recognize and bind the DNA at specific binding sites (response elements) within promoter regions associated with each gene. We present an information theoretic approach to modeling transcrip...

Full description

Bibliographic Details
Main Authors: Duygu Balcan, Alkan Kabakçioğlu, Muhittin Mungan, Ayşe Erzan
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2007-06-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0000501
id doaj-1e22e8ea33ba4996bb95cb9d8d2a6484
record_format Article
spelling doaj-1e22e8ea33ba4996bb95cb9d8d2a64842021-03-03T19:55:56ZengPublic Library of Science (PLoS)PLoS ONE1932-62032007-06-0126e50110.1371/journal.pone.0000501The information coded in the yeast response elements accounts for most of the topological properties of its transcriptional regulation network.Duygu BalcanAlkan KabakçioğluMuhittin MunganAyşe ErzanThe regulation of gene expression in a cell relies to a major extent on transcription factors, proteins which recognize and bind the DNA at specific binding sites (response elements) within promoter regions associated with each gene. We present an information theoretic approach to modeling transcriptional regulatory networks, in terms of a simple "sequence-matching" rule and the statistics of the occurrence of binding sequences of given specificity in random promoter regions. The crucial biological input is the distribution of the amount of information coded in these cognate response elements and the length distribution of the promoter regions. We provide an analysis of the transcriptional regulatory network of yeast Saccharomyces cerevisiae, which we extract from the available databases, with respect to the degree distributions, clustering coefficient, degree correlations, rich-club coefficient and the k-core structure. We find that these topological features are in remarkable agreement with those predicted by our model, on the basis of the amount of information coded in the interaction between the transcription factors and response elements.https://doi.org/10.1371/journal.pone.0000501
collection DOAJ
language English
format Article
sources DOAJ
author Duygu Balcan
Alkan Kabakçioğlu
Muhittin Mungan
Ayşe Erzan
spellingShingle Duygu Balcan
Alkan Kabakçioğlu
Muhittin Mungan
Ayşe Erzan
The information coded in the yeast response elements accounts for most of the topological properties of its transcriptional regulation network.
PLoS ONE
author_facet Duygu Balcan
Alkan Kabakçioğlu
Muhittin Mungan
Ayşe Erzan
author_sort Duygu Balcan
title The information coded in the yeast response elements accounts for most of the topological properties of its transcriptional regulation network.
title_short The information coded in the yeast response elements accounts for most of the topological properties of its transcriptional regulation network.
title_full The information coded in the yeast response elements accounts for most of the topological properties of its transcriptional regulation network.
title_fullStr The information coded in the yeast response elements accounts for most of the topological properties of its transcriptional regulation network.
title_full_unstemmed The information coded in the yeast response elements accounts for most of the topological properties of its transcriptional regulation network.
title_sort information coded in the yeast response elements accounts for most of the topological properties of its transcriptional regulation network.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2007-06-01
description The regulation of gene expression in a cell relies to a major extent on transcription factors, proteins which recognize and bind the DNA at specific binding sites (response elements) within promoter regions associated with each gene. We present an information theoretic approach to modeling transcriptional regulatory networks, in terms of a simple "sequence-matching" rule and the statistics of the occurrence of binding sequences of given specificity in random promoter regions. The crucial biological input is the distribution of the amount of information coded in these cognate response elements and the length distribution of the promoter regions. We provide an analysis of the transcriptional regulatory network of yeast Saccharomyces cerevisiae, which we extract from the available databases, with respect to the degree distributions, clustering coefficient, degree correlations, rich-club coefficient and the k-core structure. We find that these topological features are in remarkable agreement with those predicted by our model, on the basis of the amount of information coded in the interaction between the transcription factors and response elements.
url https://doi.org/10.1371/journal.pone.0000501
work_keys_str_mv AT duygubalcan theinformationcodedintheyeastresponseelementsaccountsformostofthetopologicalpropertiesofitstranscriptionalregulationnetwork
AT alkankabakcioglu theinformationcodedintheyeastresponseelementsaccountsformostofthetopologicalpropertiesofitstranscriptionalregulationnetwork
AT muhittinmungan theinformationcodedintheyeastresponseelementsaccountsformostofthetopologicalpropertiesofitstranscriptionalregulationnetwork
AT ayseerzan theinformationcodedintheyeastresponseelementsaccountsformostofthetopologicalpropertiesofitstranscriptionalregulationnetwork
AT duygubalcan informationcodedintheyeastresponseelementsaccountsformostofthetopologicalpropertiesofitstranscriptionalregulationnetwork
AT alkankabakcioglu informationcodedintheyeastresponseelementsaccountsformostofthetopologicalpropertiesofitstranscriptionalregulationnetwork
AT muhittinmungan informationcodedintheyeastresponseelementsaccountsformostofthetopologicalpropertiesofitstranscriptionalregulationnetwork
AT ayseerzan informationcodedintheyeastresponseelementsaccountsformostofthetopologicalpropertiesofitstranscriptionalregulationnetwork
_version_ 1714824902586925056