Literature DB >> 18426806

Eukaryotic transcription factor binding sites--modeling and integrative search methods.

Sridhar Hannenhalli1.   

Abstract

A comprehensive knowledge of transcription factor binding sites (TFBS) is important for a mechanistic understanding of transcriptional regulation as well as for inferring gene regulatory networks. Because the DNA motif recognized by a transcription factor is typically short and degenerate, computational approaches for identifying binding sites based only on the sequence motif inevitably suffer from high error rates. Current state-of-the-art techniques for improving computational identification of binding sites can be broadly categorized into two classes: (1) approaches that aim to improve binding motif models by extracting maximal sequence information from experimentally determined binding sites and (2) approaches that supplement binding motif models with additional genomic or other attributes (such as evolutionary conservation). In this review we will discuss recent attempts to improve computational identification of TFBS through these two types of approaches and conclude with thoughts on future development.

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Year:  2008        PMID: 18426806     DOI: 10.1093/bioinformatics/btn198

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


  46 in total

1.  Regulation of POU4F3 gene expression in hair cells by 5' DNA in mice.

Authors:  M Masuda; D Dulon; K Pak; L M Mullen; Y Li; L Erkman; A F Ryan
Journal:  Neuroscience       Date:  2011-09-19       Impact factor: 3.590

Review 2.  Identifying regulatory elements in eukaryotic genomes.

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

3.  Predicting DNA recognition by Cys2His2 zinc finger proteins.

Authors:  Anton V Persikov; Robert Osada; Mona Singh
Journal:  Bioinformatics       Date:  2008-11-13       Impact factor: 6.937

4.  Detailing regulatory networks through large scale data integration.

Authors:  Curtis Huttenhower; K Tsheko Mutungu; Natasha Indik; Woongcheol Yang; Mark Schroeder; Joshua J Forman; Olga G Troyanskaya; Hilary A Coller
Journal:  Bioinformatics       Date:  2009-10-13       Impact factor: 6.937

5.  Unusually effective microRNA targeting within repeat-rich coding regions of mammalian mRNAs.

Authors:  Michael Schnall-Levin; Olivia S Rissland; Wendy K Johnston; Norbert Perrimon; David P Bartel; Bonnie Berger
Journal:  Genome Res       Date:  2011-06-17       Impact factor: 9.043

6.  De novo prediction of DNA-binding specificities for Cys2His2 zinc finger proteins.

Authors:  Anton V Persikov; Mona Singh
Journal:  Nucleic Acids Res       Date:  2013-10-03       Impact factor: 16.971

7.  Prediction and experimental validation of novel STAT3 target genes in human cancer cells.

Authors:  Young Min Oh; Jong Kyoung Kim; Yongwook Choi; Seungjin Choi; Joo-Yeon Yoo
Journal:  PLoS One       Date:  2009-09-04       Impact factor: 3.240

8.  Genome-wide histone acetylation data improve prediction of mammalian transcription factor binding sites.

Authors:  Stephen A Ramsey; Theo A Knijnenburg; Kathleen A Kennedy; Daniel E Zak; Mark Gilchrist; Elizabeth S Gold; Carrie D Johnson; Aaron E Lampano; Vladimir Litvak; Garnet Navarro; Tetyana Stolyar; Alan Aderem; Ilya Shmulevich
Journal:  Bioinformatics       Date:  2010-07-27       Impact factor: 6.937

9.  A protein-protein interaction guided method for competitive transcription factor binding improves target predictions.

Authors:  Kirsti Laurila; Olli Yli-Harja; Harri Lähdesmäki
Journal:  Nucleic Acids Res       Date:  2009-12       Impact factor: 16.971

10.  Variable structure motifs for transcription factor binding sites.

Authors:  John E Reid; Kenneth J Evans; Nigel Dyer; Lorenz Wernisch; Sascha Ott
Journal:  BMC Genomics       Date:  2010-01-14       Impact factor: 3.969

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