Literature DB >> 12824350

REDUCE: An online tool for inferring cis-regulatory elements and transcriptional module activities from microarray data.

Crispin Roven1, Harmen J Bussemaker.   

Abstract

REDUCE is a motif-based regression method for microarray analysis. The only required inputs are (i) a single genome-wide set of absolute or relative mRNA abundances and (ii) the DNA sequence of the regulatory region associated with each gene that is probed. Currently supported organisms are yeast, worm and fly; it is an open question whether in its current incarnation our approach can be used for mouse or human. REDUCE uses unbiased statistics to identify oligonucleotide motifs whose occurrence in the regulatory region of a gene correlates with the level of mRNA expression. Regression analysis is used to infer the activity of the transcriptional module associated with each motif. REDUCE is available online at http://bussemaker.bio.columbia.edu/reduce/. This web site provides functionality for the upload and management of microarray data. REDUCE analysis results can be viewed and downloaded, and optionally be shared with other users or made publicly accessible.

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Year:  2003        PMID: 12824350      PMCID: PMC169192          DOI: 10.1093/nar/gkg630

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


  24 in total

Review 1.  Discovery and modeling of transcriptional regulatory regions.

Authors:  J W Fickett; W W Wasserman
Journal:  Curr Opin Biotechnol       Date:  2000-02       Impact factor: 9.740

2.  Regulatory element detection using correlation with expression.

Authors:  H J Bussemaker; H Li; E D Siggia
Journal:  Nat Genet       Date:  2001-02       Impact factor: 38.330

3.  Minimum information about a microarray experiment (MIAME)-toward standards for microarray data.

Authors:  A Brazma; P Hingamp; J Quackenbush; G Sherlock; P Spellman; C Stoeckert; J Aach; W Ansorge; C A Ball; H C Causton; T Gaasterland; P Glenisson; F C Holstege; I F Kim; V Markowitz; J C Matese; H Parkinson; A Robinson; U Sarkans; S Schulze-Kremer; J Stewart; R Taylor; J Vilo; M Vingron
Journal:  Nat Genet       Date:  2001-12       Impact factor: 38.330

4.  Visualizing associations between genome sequences and gene expression data using genome-mean expression profiles.

Authors:  D Y Chiang; P O Brown; M B Eisen
Journal:  Bioinformatics       Date:  2001       Impact factor: 6.937

Review 5.  Exploring the new world of the genome with DNA microarrays.

Authors:  P O Brown; D Botstein
Journal:  Nat Genet       Date:  1999-01       Impact factor: 38.330

6.  Genomic expression programs in the response of yeast cells to environmental changes.

Authors:  A P Gasch; P T Spellman; C M Kao; O Carmel-Harel; M B Eisen; G Storz; D Botstein; P O Brown
Journal:  Mol Biol Cell       Date:  2000-12       Impact factor: 4.138

Review 7.  Functional genomics as applied to mapping transcription regulatory networks.

Authors:  Nila Banerjee; Michael Q Zhang
Journal:  Curr Opin Microbiol       Date:  2002-06       Impact factor: 7.934

8.  Dissection of transient oxidative stress response in Saccharomyces cerevisiae by using DNA microarrays.

Authors:  Marian Groot Koerkamp; Martijn Rep; Harmen J Bussemaker; Guy P M A Hardy; Adri Mul; Kasia Piekarska; Cristina Al-Khalili Szigyarto; Joost M Teixeira De Mattos; Henk F Tabak
Journal:  Mol Biol Cell       Date:  2002-08       Impact factor: 4.138

9.  Identification of regulatory elements using a feature selection method.

Authors:  Sündüz Keleş; Mark van der Laan; Michael B Eisen
Journal:  Bioinformatics       Date:  2002-09       Impact factor: 6.937

10.  Design and implementation of microarray gene expression markup language (MAGE-ML).

Authors:  Paul T Spellman; Michael Miller; Jason Stewart; Charles Troup; Ugis Sarkans; Steve Chervitz; Derek Bernhart; Gavin Sherlock; Catherine Ball; Marc Lepage; Marcin Swiatek; W L Marks; Jason Goncalves; Scott Markel; Daniel Iordan; Mohammadreza Shojatalab; Angel Pizarro; Joe White; Robert Hubley; Eric Deutsch; Martin Senger; Bruce J Aronow; Alan Robinson; Doug Bassett; Christian J Stoeckert; Alvis Brazma
Journal:  Genome Biol       Date:  2002-08-23       Impact factor: 13.583

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  23 in total

Review 1.  Charting gene regulatory networks: strategies, challenges and perspectives.

Authors:  Gong-Hong Wei; De-Pei Liu; Chih-Chuan Liang
Journal:  Biochem J       Date:  2004-07-01       Impact factor: 3.857

2.  Early expression of yeast genes affected by chemical stress.

Authors:  A Lucau-Danila; G Lelandais; Z Kozovska; V Tanty; T Delaveau; F Devaux; C Jacq
Journal:  Mol Cell Biol       Date:  2005-03       Impact factor: 4.272

3.  Bayesian error analysis model for reconstructing transcriptional regulatory networks.

Authors:  Ning Sun; Raymond J Carroll; Hongyu Zhao
Journal:  Proc Natl Acad Sci U S A       Date:  2006-05-15       Impact factor: 11.205

4.  Experimentally based contact energies decode interactions responsible for protein-DNA affinity and the role of molecular waters at the binding interface.

Authors:  N Alpay Temiz; Carlos J Camacho
Journal:  Nucleic Acids Res       Date:  2009-05-08       Impact factor: 16.971

5.  Assigning roles to DNA regulatory motifs using comparative genomics.

Authors:  Fabian A Buske; Mikael Bodén; Denis C Bauer; Timothy L Bailey
Journal:  Bioinformatics       Date:  2010-02-10       Impact factor: 6.937

6.  MTAP: the motif tool assessment platform.

Authors:  Daniel Quest; Kathryn Dempsey; Mohammad Shafiullah; Dhundy Bastola; Hesham Ali
Journal:  BMC Bioinformatics       Date:  2008-08-12       Impact factor: 3.169

7.  RNAcompete methodology and application to determine sequence preferences of unconventional RNA-binding proteins.

Authors:  Debashish Ray; Kevin C H Ha; Kate Nie; Hong Zheng; Timothy R Hughes; Quaid D Morris
Journal:  Methods       Date:  2016-12-10       Impact factor: 3.608

8.  Computational modeling of in vivo and in vitro protein-DNA interactions by multiple instance learning.

Authors:  Zhen Gao; Jianhua Ruan
Journal:  Bioinformatics       Date:  2017-07-15       Impact factor: 6.937

9.  Motif discovery and transcription factor binding sites before and after the next-generation sequencing era.

Authors:  Federico Zambelli; Graziano Pesole; Giulio Pavesi
Journal:  Brief Bioinform       Date:  2012-04-19       Impact factor: 11.622

10.  Discovery of protein-DNA interactions by penalized multivariate regression.

Authors:  Leonid Zamdborg; Ping Ma
Journal:  Nucleic Acids Res       Date:  2009-07-03       Impact factor: 16.971

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