Literature DB >> 14516744

Correlating protein-DNA and protein-protein interaction networks.

Thomas Manke1, Ricardo Bringas, Martin Vingron.   

Abstract

Here, we search protein-DNA binding data for prevalent pairs and higher-order tuples of co-occurring transcription factors (TF) in Saccharomyces cerevisiae. While the identification of such modules is dependent on uncertainties of genome-wide data sets, we find several biologically meaningful examples, which allow putative annotation of yet unclassified genes. For the frequently occurring transcriptional module Mcm1-Fkh2-Ndd1, we identified several new target genes involved in cell-cycle control and filament formation. Using large-scale protein interaction data, we demonstrate a significant correlation between co-occurrence of TF binding sites and the vicinity in the protein interaction network. In particular we find that directly interacting transcription factors and those which are members of a protein complex are more likely to occur together as putative DNA-binding modules.

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Year:  2003        PMID: 14516744     DOI: 10.1016/j.jmb.2003.08.004

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  15 in total

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2.  Transcriptional regulation of protein complexes within and across species.

Authors:  Kai Tan; Tomer Shlomi; Hoda Feizi; Trey Ideker; Roded Sharan
Journal:  Proc Natl Acad Sci U S A       Date:  2007-01-16       Impact factor: 11.205

3.  cDREM: inferring dynamic combinatorial gene regulation.

Authors:  Aaron Wise; Ziv Bar-Joseph
Journal:  J Comput Biol       Date:  2015-04       Impact factor: 1.479

4.  Function, dynamics and evolution of network motif modules in integrated gene regulatory networks of worm and plant.

Authors:  Jonas Defoort; Yves Van de Peer; Vanessa Vermeirssen
Journal:  Nucleic Acids Res       Date:  2018-07-27       Impact factor: 16.971

5.  From gene networks to gene function.

Authors:  Thomas Schlitt; Kimmo Palin; Johan Rung; Sabine Dietmann; Michael Lappe; Esko Ukkonen; Alvis Brazma
Journal:  Genome Res       Date:  2003-12       Impact factor: 9.043

6.  Identification and analysis of co-occurrence networks with NetCutter.

Authors:  Heiko Müller; Francesco Mancuso
Journal:  PLoS One       Date:  2008-09-10       Impact factor: 3.240

7.  Detection of interacting transcription factors in human tissues using predicted DNA binding affinity.

Authors:  Alena Myšičková; Martin Vingron
Journal:  BMC Genomics       Date:  2012-01-17       Impact factor: 3.969

8.  Transcription factor and chromatin features predict genes associated with eQTLs.

Authors:  Dennis Wang; Augusto Rendon; Lorenz Wernisch
Journal:  Nucleic Acids Res       Date:  2012-12-28       Impact factor: 16.971

9.  Combinatorial binding in human and mouse embryonic stem cells identifies conserved enhancers active in early embryonic development.

Authors:  Jonathan Göke; Marc Jung; Sarah Behrens; Lukas Chavez; Sean O'Keeffe; Bernd Timmermann; Hans Lehrach; James Adjaye; Martin Vingron
Journal:  PLoS Comput Biol       Date:  2011-12-22       Impact factor: 4.475

10.  Prioritization of gene regulatory interactions from large-scale modules in yeast.

Authors:  Ho-Joon Lee; Thomas Manke; Ricardo Bringas; Martin Vingron
Journal:  BMC Bioinformatics       Date:  2008-01-22       Impact factor: 3.169

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