Literature DB >> 15759656

Modulefinder: a tool for computational discovery of cis regulatory modules.

Anthony A Philippakis1, Fangxue Sherry He, Martha L Bulyk.   

Abstract

Regulation of gene expression occurs largely through the binding of sequence-specific transcription factors (TFs) to genomic binding sites (BSs). We present a rigorous scoring scheme, implemented as a C program termed "ModuleFinder", that evaluates the likelihood that a given genomic region is a cis regulatory module (CRM) for an input set of TFs according to its degree of: (1) homotypic site clustering; (2) heterotypic site clustering; and (3) evolutionary conservation across multiple genomes. Importantly, ModuleFinder obtains all parameters needed to appropriately weight the relative contributions of these sequence features directly from the input sequences and TFBS motifs, and does not need to first be trained. Using two previously described collections of experimentally verified CRMs in mammals and in fly as validation datasets, we show that ModuleFinder is able to identify CRMs with great sensitivity and specificity.

Mesh:

Substances:

Year:  2005        PMID: 15759656      PMCID: PMC2692613     

Source DB:  PubMed          Journal:  Pac Symp Biocomput        ISSN: 2335-6928


  25 in total

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Authors:  G D Stormo
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5.  Conservation of DNA regulatory motifs and discovery of new motifs in microbial genomes.

Authors:  A M McGuire; J D Hughes; G M Church
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6.  Human-mouse genome comparisons to locate regulatory sites.

Authors:  W W Wasserman; M Palumbo; W Thompson; J W Fickett; C E Lawrence
Journal:  Nat Genet       Date:  2000-10       Impact factor: 38.330

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8.  Determination of the consensus binding site for MEF2 expressed in muscle and brain reveals tissue-specific sequence constraints.

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10.  Sequencing and comparison of yeast species to identify genes and regulatory elements.

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  22 in total

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Authors:  Sonali Mukherjee; Michael F Berger; Ghil Jona; Xun S Wang; Dale Muzzey; Michael Snyder; Richard A Young; Martha L Bulyk
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2.  LOESS correction for length variation in gene set-based genomic sequence analysis.

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3.  Genome-wide computational prediction of transcriptional regulatory modules reveals new insights into human gene expression.

Authors:  Mathieu Blanchette; Alain R Bataille; Xiaoyu Chen; Christian Poitras; Josée Laganière; Céline Lefèbvre; Geneviève Deblois; Vincent Giguère; Vincent Ferretti; Dominique Bergeron; Benoit Coulombe; François Robert
Journal:  Genome Res       Date:  2006-04-10       Impact factor: 9.043

Review 4.  Applying whole-genome studies of epigenetic regulation to study human disease.

Authors:  J D Lieb; S Beck; M L Bulyk; P Farnham; N Hattori; S Henikoff; X S Liu; K Okumura; K Shiota; T Ushijima; J M Greally
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Review 5.  Identifying regulatory elements in eukaryotic genomes.

Authors:  Leelavati Narlikar; Ivan Ovcharenko
Journal:  Brief Funct Genomic Proteomic       Date:  2009-06-04

6.  Genome-wide identification of conserved regulatory function in diverged sequences.

Authors:  Leila Taher; David M McGaughey; Samantha Maragh; Ivy Aneas; Seneca L Bessling; Webb Miller; Marcelo A Nobrega; Andrew S McCallion; Ivan Ovcharenko
Journal:  Genome Res       Date:  2011-05-31       Impact factor: 9.043

7.  A novel method for predicting activity of cis-regulatory modules, based on a diverse training set.

Authors:  Wei Yang; Saurabh Sinha
Journal:  Bioinformatics       Date:  2016-09-07       Impact factor: 6.937

8.  Quantitative modeling of a gene's expression from its intergenic sequence.

Authors:  Md Abul Hassan Samee; Saurabh Sinha
Journal:  PLoS Comput Biol       Date:  2014-03-06       Impact factor: 4.475

Review 9.  Integrating sequence, evolution and functional genomics in regulatory genomics.

Authors:  Martin Vingron; Alvis Brazma; Richard Coulson; Jacques van Helden; Thomas Manke; Kimmo Palin; Olivier Sand; Esko Ukkonen
Journal:  Genome Biol       Date:  2009-01-30       Impact factor: 13.583

10.  Finding evolutionarily conserved cis-regulatory modules with a universal set of motifs.

Authors:  Bartek Wilczynski; Norbert Dojer; Mateusz Patelak; Jerzy Tiuryn
Journal:  BMC Bioinformatics       Date:  2009-03-10       Impact factor: 3.169

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