Literature DB >> 16431075

Condition-specific coregulation with cis-regulatory motifs and modules in the mouse genome.

Dongseok Choi1, Yuan Fang, William D Mathers.   

Abstract

Deciphering genetic regulatory codes remains a challenge. Here, we present an effective approach to identifying in vivo condition-specific coregulation with cis-regulatory motifs and modules in the mouse genome. A resampling-based algorithm was adopted to cluster our microarray data of a stress response, which generated 35 tight clusters with unique expression patterns containing 811 genes of 5652 genes significantly altered. Database searches identified many known motifs within the 3-kb regulatory regions of 40 genes from 3 clusters and modules with six to nine motifs that were commonly shared by 60-100% of these genes. The upstream regulatory region contained the highest frequency of these common motifs. CisModule program predictions were comparable with the results from database searches and found four potentially novel motifs. This result indicates that these motifs and modules could be responsible for gene coregulation of the stress response in the lacrimal gland.

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Year:  2006        PMID: 16431075     DOI: 10.1016/j.ygeno.2005.11.015

Source DB:  PubMed          Journal:  Genomics        ISSN: 0888-7543            Impact factor:   5.736


  4 in total

1.  Application of Biostatistics and Bioinformatics Tools to Identify Putative Transcription Factor-Gene Regulatory Network of Ankylosing Spondylitis and Sarcoidosis.

Authors:  Dongseok Choi; Srilakshmi M Sharma; Sirichai Pasadhika; Zhixin Kang; Christina A Harrington; Justine R Smith; Stephen R Planck; James T Rosenbaum
Journal:  Commun Stat Theory Methods       Date:  2009-01-01       Impact factor: 0.893

2.  Computational identification of transcriptional regulators in human endotoxemia.

Authors:  Tung T Nguyen; Panagiota T Foteinou; Steven E Calvano; Stephen F Lowry; Ioannis P Androulakis
Journal:  PLoS One       Date:  2011-05-27       Impact factor: 3.240

3.  Transcription factor site dependencies in human, mouse and rat genomes.

Authors:  Andrija Tomovic; Michael Stadler; Edward J Oakeley
Journal:  BMC Bioinformatics       Date:  2009-10-16       Impact factor: 3.169

4.  A genome-wide screen indicates correlation between differentiation and expression of metabolism related genes.

Authors:  Priti Roy; Brijesh Kumar; Akhilesh Shende; Anupama Singh; Anil Meena; Ritika Ghosal; Madhav Ranganathan; Amitabha Bandyopadhyay
Journal:  PLoS One       Date:  2013-05-22       Impact factor: 3.240

  4 in total

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