Literature DB >> 15699025

A comparative analysis of relative occurrence of transcription factor binding sites in vertebrate genomes and gene promoter areas.

Maria Stepanova1, Tatiana Tiazhelova, Mikle Skoblov, Ancha Baranova.   

Abstract

MOTIVATION: The detection of transcription factor binding sites (TFBS) in genomic sequences is a basic task for elucidating the transcriptional aspects of gene regulation. Evaluation procedures applicable to the TFBS prediction outputs need improvement. Predicted TFBS located outside of the transcription associated areas are often neglected from the functional and the evolutionary points of view, therefore deserving a systematic overview.
RESULTS: We calculated theoretical occurrences of 184 TFBS according to their position weight matrices and the dinucleotide statistics of the completed vertebrate genomes, then performed a TFBS prediction in the corresponding complete genomic sequences and their repeat-free, repetitive and regulatory fractions. Repeat-free fractions of the closely related mammalian genomes were characterized by strong similarities in TFBS occurrences. A significant over-representation of multiple TFBS was found in both repetitive and non-repetitive genome fractions. AVAILABILITY: F-values and real TFBS occurrences calculated for human, chimp, mouse, rat, zebrafish and fugu genomes are available for free download at http://www.gmu.edu/departments/mmb/baranova/pages/bioinformatics

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Year:  2005        PMID: 15699025     DOI: 10.1093/bioinformatics/bti307

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  11 in total

1.  A transcription factor affinity-based code for mammalian transcription initiation.

Authors:  Molly Megraw; Fernando Pereira; Shane T Jensen; Uwe Ohler; Artemis G Hatzigeorgiou
Journal:  Genome Res       Date:  2009-01-13       Impact factor: 9.043

2.  Pathways of aging: comparative analysis of gene signatures in replicative senescence and stress induced premature senescence.

Authors:  Kamil C Kural; Neetu Tandon; Mikhail Skoblov; Olga V Kel-Margoulis; Ancha V Baranova
Journal:  BMC Genomics       Date:  2016-12-28       Impact factor: 3.969

3.  Human RFP2 gene promoter: unique structure and unusual strength.

Authors:  Mikhail Skoblov; Konstantin Shakhbazov; Dmitry Oshchepkov; Dmitry Ivanov; Anna Guskova; Dmitry Ivanov; Petr Rubtsov; Vladimir Prasolov; Nick Yankovsky; Ancha Baranova
Journal:  Biochem Biophys Res Commun       Date:  2006-02-17       Impact factor: 3.575

4.  Human promoter genomic composition demonstrates non-random groupings that reflect general cellular function.

Authors:  Markey C McNutt; Ron Tongbai; Wenwu Cui; Irene Collins; Wendy J Freebern; Idalia Montano; Cynthia M Haggerty; Gvr Chandramouli; Kevin Gardner
Journal:  BMC Bioinformatics       Date:  2005-10-18       Impact factor: 3.169

5.  In silico modelling of hormone response elements.

Authors:  Maria Stepanova; Feng Lin; Valerie C-L Lin
Journal:  BMC Bioinformatics       Date:  2006-12-12       Impact factor: 3.169

6.  Alu elements contain many binding sites for transcription factors and may play a role in regulation of developmental processes.

Authors:  Paz Polak; Eytan Domany
Journal:  BMC Genomics       Date:  2006-06-01       Impact factor: 3.969

7.  MicroRNAs enrichment in GWAS of complex human phenotypes.

Authors:  Luiz F Goulart; Francesco Bettella; Ida E Sønderby; Andrew J Schork; Wesley K Thompson; Morten Mattingsdal; Vidar M Steen; Verena Zuber; Yunpeng Wang; Anders M Dale; Ole A Andreassen; Srdjan Djurovic
Journal:  BMC Genomics       Date:  2015-04-16       Impact factor: 3.969

Review 8.  Computational Identification of Novel Genes: Current and Future Perspectives.

Authors:  Steffen Klasberg; Tristan Bitard-Feildel; Ludovic Mallet
Journal:  Bioinform Biol Insights       Date:  2016-08-01

9.  Nucleotide patterns aiding in prediction of eukaryotic promoters.

Authors:  Martin Triska; Victor Solovyev; Ancha Baranova; Alexander Kel; Tatiana V Tatarinova
Journal:  PLoS One       Date:  2017-11-15       Impact factor: 3.240

10.  Determining significance of pairwise co-occurrences of events in bursty sequences.

Authors:  Niina Haiminen; Heikki Mannila; Evimaria Terzi
Journal:  BMC Bioinformatics       Date:  2008-08-08       Impact factor: 3.169

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