Literature DB >> 21632251

Reconstructing regulatory network transitions.

Jalean J Petricka1, Philip N Benfey.   

Abstract

Cellular responses often involve a transition of cells from one state to another. A transition from a stem cell to a differentiated cell state, for example, might occur in response to gene expression changes induced by a transcription factor, or to signaling cascades triggered by a hormone or pathogen. Regulatory networks are thought to control such cellular transitions. Thus, many researchers are interested in reconstructing regulatory networks, not only with the aim of gaining a deeper understanding of cellular transitions, but also of using networks to predict and potentially manipulate cellular transitions and outcomes. In this review, we highlight approaches to the reconstruction of regulatory networks underlying cellular transitions, with special attention to transcriptional regulatory networks. We describe recent regulatory network reconstructions in a variety of organisms, and discuss the success they share in identifying new regulatory components, shared relationships and phenotypic outcomes.
Copyright © 2011 Elsevier Ltd. All rights reserved.

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Year:  2011        PMID: 21632251      PMCID: PMC3149721          DOI: 10.1016/j.tcb.2011.05.001

Source DB:  PubMed          Journal:  Trends Cell Biol        ISSN: 0962-8924            Impact factor:   20.808


  42 in total

1.  Serial regulation of transcriptional regulators in the yeast cell cycle.

Authors:  I Simon; J Barnett; N Hannett; C T Harbison; N J Rinaldi; T L Volkert; J J Wyrick; J Zeitlinger; D K Gifford; T S Jaakkola; R A Young
Journal:  Cell       Date:  2001-09-21       Impact factor: 41.582

2.  Systems biology: understanding cells.

Authors:  Paul Nurse
Journal:  Nature       Date:  2003-08-21       Impact factor: 49.962

3.  Core transcriptional regulatory circuitry in human embryonic stem cells.

Authors:  Laurie A Boyer; Tong Ihn Lee; Megan F Cole; Sarah E Johnstone; Stuart S Levine; Jacob P Zucker; Matthew G Guenther; Roshan M Kumar; Heather L Murray; Richard G Jenner; David K Gifford; Douglas A Melton; Rudolf Jaenisch; Richard A Young
Journal:  Cell       Date:  2005-09-23       Impact factor: 41.582

Review 4.  Genome-wide transcription factor binding: beyond direct target regulation.

Authors:  Kyle L MacQuarrie; Abraham P Fong; Randall H Morse; Stephen J Tapscott
Journal:  Trends Genet       Date:  2011-02-04       Impact factor: 11.639

5.  Evolution of transcription factors and the gene regulatory network in Escherichia coli.

Authors:  M Madan Babu; Sarah A Teichmann
Journal:  Nucleic Acids Res       Date:  2003-02-15       Impact factor: 16.971

6.  Correlation between protein and mRNA abundance in yeast.

Authors:  S P Gygi; Y Rochon; B R Franza; R Aebersold
Journal:  Mol Cell Biol       Date:  1999-03       Impact factor: 4.272

7.  Global analysis of protein expression in yeast.

Authors:  Sina Ghaemmaghami; Won-Ki Huh; Kiowa Bower; Russell W Howson; Archana Belle; Noah Dephoure; Erin K O'Shea; Jonathan S Weissman
Journal:  Nature       Date:  2003-10-16       Impact factor: 49.962

8.  Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization.

Authors:  P T Spellman; G Sherlock; M Q Zhang; V R Iyer; K Anders; M B Eisen; P O Brown; D Botstein; B Futcher
Journal:  Mol Biol Cell       Date:  1998-12       Impact factor: 4.138

9.  Transcriptional regulatory code of a eukaryotic genome.

Authors:  Christopher T Harbison; D Benjamin Gordon; Tong Ihn Lee; Nicola J Rinaldi; Kenzie D Macisaac; Timothy W Danford; Nancy M Hannett; Jean-Bosco Tagne; David B Reynolds; Jane Yoo; Ezra G Jennings; Julia Zeitlinger; Dmitry K Pokholok; Manolis Kellis; P Alex Rolfe; Ken T Takusagawa; Eric S Lander; David K Gifford; Ernest Fraenkel; Richard A Young
Journal:  Nature       Date:  2004-09-02       Impact factor: 49.962

10.  Transcriptional regulatory networks in Saccharomyces cerevisiae.

Authors:  Tong Ihn Lee; Nicola J Rinaldi; François Robert; Duncan T Odom; Ziv Bar-Joseph; Georg K Gerber; Nancy M Hannett; Christopher T Harbison; Craig M Thompson; Itamar Simon; Julia Zeitlinger; Ezra G Jennings; Heather L Murray; D Benjamin Gordon; Bing Ren; John J Wyrick; Jean-Bosco Tagne; Thomas L Volkert; Ernest Fraenkel; David K Gifford; Richard A Young
Journal:  Science       Date:  2002-10-25       Impact factor: 47.728

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  16 in total

Review 1.  Control of Arabidopsis root development.

Authors:  Jalean J Petricka; Cara M Winter; Philip N Benfey
Journal:  Annu Rev Plant Biol       Date:  2012-02-09       Impact factor: 26.379

2.  The protein expression landscape of the Arabidopsis root.

Authors:  Jalean J Petricka; Monica A Schauer; Molly Megraw; Natalie W Breakfield; J Will Thompson; Stoyan Georgiev; Erik J Soderblom; Uwe Ohler; Martin Arthur Moseley; Ueli Grossniklaus; Philip N Benfey
Journal:  Proc Natl Acad Sci U S A       Date:  2012-03-23       Impact factor: 11.205

3.  Reconstruction of protein networks from an atlas of maize seed proteotypes.

Authors:  Justin W Walley; Zhouxin Shen; Ryan Sartor; Kevin J Wu; Joshua Osborn; Laurie G Smith; Steven P Briggs
Journal:  Proc Natl Acad Sci U S A       Date:  2013-11-18       Impact factor: 11.205

Review 4.  Perimenopause as a neurological transition state.

Authors:  Roberta D Brinton; Jia Yao; Fei Yin; Wendy J Mack; Enrique Cadenas
Journal:  Nat Rev Endocrinol       Date:  2015-05-26       Impact factor: 43.330

Review 5.  Epigenetics of the developing and aging brain: Mechanisms that regulate onset and outcomes of brain reorganization.

Authors:  Eliza R Bacon; Roberta Diaz Brinton
Journal:  Neurosci Biobehav Rev       Date:  2021-02-28       Impact factor: 8.989

6.  Transcript profiling of cytokinin action in Arabidopsis roots and shoots discovers largely similar but also organ-specific responses.

Authors:  Wolfram G Brenner; Thomas Schmülling
Journal:  BMC Plant Biol       Date:  2012-07-23       Impact factor: 4.215

7.  Modeling regulatory cascades using Artificial Neural Networks: the case of transcriptional regulatory networks shaped during the yeast stress response.

Authors:  Maria E Manioudaki; Panayiota Poirazi
Journal:  Front Genet       Date:  2013-06-20       Impact factor: 4.599

8.  An Integrated Statistical Approach to Compare Transcriptomics Data Across Experiments: A Case Study on the Identification of Candidate Target Genes of the Transcription Factor PPARα.

Authors:  Mohammad Ohid Ullah; Michael Müller; Guido J E J Hooiveld
Journal:  Bioinform Biol Insights       Date:  2012-06-19

9.  An experimentally validated network of nine haematopoietic transcription factors reveals mechanisms of cell state stability.

Authors:  Judith Schütte; Huange Wang; Stella Antoniou; Andrew Jarratt; Nicola K Wilson; Joey Riepsaame; Fernando J Calero-Nieto; Victoria Moignard; Silvia Basilico; Sarah J Kinston; Rebecca L Hannah; Mun Chiang Chan; Sylvia T Nürnberg; Willem H Ouwehand; Nicola Bonzanni; Marella Ftr de Bruijn; Berthold Göttgens
Journal:  Elife       Date:  2016-02-22       Impact factor: 8.140

10.  Stochastic simulation for the inference of transcriptional control network of yeast cyclins genes.

Authors:  Jiri Vohradsky
Journal:  Nucleic Acids Res       Date:  2012-05-15       Impact factor: 16.971

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