Literature DB >> 19381525

Methods to reconstruct and compare transcriptional regulatory networks.

M Madan Babu1, Benjamin Lang, L Aravind.   

Abstract

The availability of completely sequenced genomes and the wealth of literature on gene regulation have enabled researchers to model the transcriptional regulation system of some organisms in the form of a network. In order to reconstruct such networks in non-model organisms, three principal approaches have been taken. First, one can transfer the interactions between homologous components from a model organism to the organism of interest. Second, microarray experiments can be used to detect patterns in gene expression that stem from regulatory interactions. Finally, knowledge of experimentally characterized transcription factor binding sites can be used to analyze the promoter sequences in a genome in order to identify potential binding sites. In this chapter, we will focus in detail on the first approach and describe methods to reconstruct and analyze the transcriptional regulatory networks of uncharacterized organisms by using a known regulatory network as a template.

Mesh:

Year:  2009        PMID: 19381525     DOI: 10.1007/978-1-59745-243-4_8

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  22 in total

1.  Transcriptional regulatory networks in Arabidopsis thaliana during single and combined stresses.

Authors:  Pankaj Barah; Mahantesha Naika B N; Naresh Doni Jayavelu; Ramanathan Sowdhamini; Khader Shameer; Atle M Bones
Journal:  Nucleic Acids Res       Date:  2015-12-17       Impact factor: 16.971

Review 2.  Mechanisms and evolution of control logic in prokaryotic transcriptional regulation.

Authors:  Sacha A F T van Hijum; Marnix H Medema; Oscar P Kuipers
Journal:  Microbiol Mol Biol Rev       Date:  2009-09       Impact factor: 11.056

3.  Every Site Counts: Submitting Transcription Factor-Binding Site Information through the CollecTF Portal.

Authors:  Ivan Erill
Journal:  J Bacteriol       Date:  2015-05-26       Impact factor: 3.490

4.  DREAM3: network inference using dynamic context likelihood of relatedness and the inferelator.

Authors:  Aviv Madar; Alex Greenfield; Eric Vanden-Eijnden; Richard Bonneau
Journal:  PLoS One       Date:  2010-03-22       Impact factor: 3.240

Review 5.  Synthetic biology: tools to design, build, and optimize cellular processes.

Authors:  Eric Young; Hal Alper
Journal:  J Biomed Biotechnol       Date:  2010-01-27

Review 6.  Built shallow to maintain homeostasis and persistent infection: insight into the transcriptional regulatory network of the gastric human pathogen Helicobacter pylori.

Authors:  Alberto Danielli; Gabriele Amore; Vincenzo Scarlato
Journal:  PLoS Pathog       Date:  2010-06-10       Impact factor: 6.823

7.  Functional enrichment analyses and construction of functional similarity networks with high confidence function prediction by PFP.

Authors:  Troy Hawkins; Meghana Chitale; Daisuke Kihara
Journal:  BMC Bioinformatics       Date:  2010-05-19       Impact factor: 3.169

8.  Genomic reconstruction of the transcriptional regulatory network in Bacillus subtilis.

Authors:  Semen A Leyn; Marat D Kazanov; Natalia V Sernova; Ekaterina O Ermakova; Pavel S Novichkov; Dmitry A Rodionov
Journal:  J Bacteriol       Date:  2013-03-15       Impact factor: 3.490

9.  Integrating external biological knowledge in the construction of regulatory networks from time-series expression data.

Authors:  Kenneth Lo; Adrian E Raftery; Kenneth M Dombek; Jun Zhu; Eric E Schadt; Roger E Bumgarner; Ka Yee Yeung
Journal:  BMC Syst Biol       Date:  2012-08-16

Review 10.  A dynamic and intricate regulatory network determines Pseudomonas aeruginosa virulence.

Authors:  Deepak Balasubramanian; Lisa Schneper; Hansi Kumari; Kalai Mathee
Journal:  Nucleic Acids Res       Date:  2012-11-11       Impact factor: 16.971

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