Literature DB >> 11928475

Automatic annotation of genomic regulatory sequences by searching for composite clusters.

O V Kel-Margoulis1, T G Ivanova, E Wingender, A E Kel.   

Abstract

A new method was developed for revealing of composite clusters of cis-elements in promoters of eukaryotic genes that are functionally related or coexpressed. A software system "ClusterScan" have been created that enables: (i) to train system on representative samples of promoters to reveal cis-elements that tend to cluster, (ii) to train system on a number of samples of functionally related promoters to identify functionally coupled transcription factors; (iii) to provide tools for searching of this clusters in genomic sequences to identify and functionally characterize regulatory regions in genome. A number of training samples of different functional and structural groups of promoters were analysed. Search for composite clusters in human chromosomes 21 and 22 reveals a number of interesting examples. Finally, a decision tree system was constructed to classify promoters of several functionally related gene groups. The decision tree system enables to identify new promoters and computationally predict their possible function.

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Year:  2002        PMID: 11928475     DOI: 10.1142/9789812799623_0018

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


  10 in total

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2.  CREME: Cis-Regulatory Module Explorer for the human genome.

Authors:  Roded Sharan; Asa Ben-Hur; Gabriela G Loots; Ivan Ovcharenko
Journal:  Nucleic Acids Res       Date:  2004-07-01       Impact factor: 16.971

3.  Assessing computational methods of cis-regulatory module prediction.

Authors:  Jing Su; Sarah A Teichmann; Thomas A Down
Journal:  PLoS Comput Biol       Date:  2010-12-02       Impact factor: 4.475

4.  A survey of motif discovery methods in an integrated framework.

Authors:  Geir Kjetil Sandve; Finn Drabløs
Journal:  Biol Direct       Date:  2006-04-06       Impact factor: 4.540

5.  Composite Module Analyst: identification of transcription factor binding site combinations using genetic algorithm.

Authors:  T Waleev; D Shtokalo; T Konovalova; N Voss; E Cheremushkin; P Stegmaier; O Kel-Margoulis; E Wingender; A Kel
Journal:  Nucleic Acids Res       Date:  2006-07-01       Impact factor: 16.971

6.  GANN: genetic algorithm neural networks for the detection of conserved combinations of features in DNA.

Authors:  Robert G Beiko; Robert L Charlebois
Journal:  BMC Bioinformatics       Date:  2005-02-22       Impact factor: 3.169

7.  A class of genes in the HER2 regulon that is poised for transcription in breast cancer cell lines and expressed in human breast tumors.

Authors:  Farah B Rahmatpanah; Zhenyu Jia; Xin Chen; Jessica E Char; Bozhao Men; Anna-Clara Franke; Frank E Jones; Michael McClelland; Dan Mercola
Journal:  Oncotarget       Date:  2015-01-20

8.  Phylogenetically and spatially conserved word pairs associated with gene-expression changes in yeasts.

Authors:  Derek Y Chiang; Alan M Moses; Manolis Kellis; Eric S Lander; Michael B Eisen
Journal:  Genome Biol       Date:  2003-06-26       Impact factor: 13.583

9.  Genome wide prediction of HNF4alpha functional binding sites by the use of local and global sequence context.

Authors:  Alexander E Kel; Monika Niehof; Volker Matys; Rüdiger Zemlin; Jürgen Borlak
Journal:  Genome Biol       Date:  2008-02-21       Impact factor: 13.583

10.  Comparative analysis of regulatory motif discovery tools for transcription factor binding sites.

Authors:  Wei Wei; Xiao-Dan Yu
Journal:  Genomics Proteomics Bioinformatics       Date:  2007-05       Impact factor: 7.691

  10 in total

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