Literature DB >> 16280626

Computational architecture of the yeast regulatory network.

Sergei Maslov1, Kim Sneppen.   

Abstract

The topology of regulatory networks contains clues to their overall design principles and evolutionary history. We find that while in- and out-degrees of a given protein in the regulatory network are not correlated with each other, there exists a strong negative correlation between the out-degree of a regulatory protein and in-degrees of its targets. Such correlation positions large regulatory modules on the periphery of the network and makes them rather well separated from each other. We also address the question of relative importance of different classes of proteins quantified by the lethality of null-mutants lacking one of them as well as by the level of their evolutionary conservation. It was found that in the yeast regulatory network highly connected proteins are in fact less important than their low-connected counterparts.

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Year:  2005        PMID: 16280626     DOI: 10.1088/1478-3975/2/4/S03

Source DB:  PubMed          Journal:  Phys Biol        ISSN: 1478-3967            Impact factor:   2.583


  9 in total

1.  Comparing genomes to computer operating systems in terms of the topology and evolution of their regulatory control networks.

Authors:  Koon-Kiu Yan; Gang Fang; Nitin Bhardwaj; Roger P Alexander; Mark Gerstein
Journal:  Proc Natl Acad Sci U S A       Date:  2010-05-03       Impact factor: 11.205

2.  Degree dependence in rates of transcription factor evolution explains the unusual structure of transcription networks.

Authors:  Alexander J Stewart; Robert M Seymour; Andrew Pomiankowski
Journal:  Proc Biol Sci       Date:  2009-04-08       Impact factor: 5.349

3.  Analysis of diverse regulatory networks in a hierarchical context shows consistent tendencies for collaboration in the middle levels.

Authors:  Nitin Bhardwaj; Koon-Kiu Yan; Mark B Gerstein
Journal:  Proc Natl Acad Sci U S A       Date:  2010-03-29       Impact factor: 11.205

4.  Activating and inhibiting connections in biological network dynamics.

Authors:  Daniel McDonald; Laura Waterbury; Rob Knight; M D Betterton
Journal:  Biol Direct       Date:  2008-12-04       Impact factor: 4.540

5.  Transcription factor binding site positioning in yeast: proximal promoter motifs characterize TATA-less promoters.

Authors:  Ionas Erb; Erik van Nimwegen
Journal:  PLoS One       Date:  2011-09-09       Impact factor: 3.240

6.  Construction and analysis of an integrated regulatory network derived from high-throughput sequencing data.

Authors:  Chao Cheng; Koon-Kiu Yan; Woochang Hwang; Jiang Qian; Nitin Bhardwaj; Joel Rozowsky; Zhi John Lu; Wei Niu; Pedro Alves; Masaomi Kato; Michael Snyder; Mark Gerstein
Journal:  PLoS Comput Biol       Date:  2011-11-17       Impact factor: 4.475

7.  Genomic analysis reveals a tight link between transcription factor dynamics and regulatory network architecture.

Authors:  Raja Jothi; S Balaji; Arthur Wuster; Joshua A Grochow; Jörg Gsponer; Teresa M Przytycka; L Aravind; M Madan Babu
Journal:  Mol Syst Biol       Date:  2009-08-18       Impact factor: 11.429

8.  One hub-one process: a tool based view on regulatory network topology.

Authors:  Jacob Bock Axelsen; Sebastian Bernhardsson; Kim Sneppen
Journal:  BMC Syst Biol       Date:  2008-03-04

9.  A system for generating transcription regulatory networks with combinatorial control of transcription.

Authors:  Sushmita Roy; Margaret Werner-Washburne; Terran Lane
Journal:  Bioinformatics       Date:  2008-04-08       Impact factor: 6.937

  9 in total

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