Combining frequency and positional information to predict transcription factor binding sites

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چکیده

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Combining frequency and positional information to predict transcription factor binding sites

MOTIVATION Even though a number of genome projects have been finished on the sequence level, still only a small proportion of DNA regulatory elements have been identified. Growing amounts of gene expression data provide the possibility of finding coregulated genes by clustering methods. By analysis of the promoter regions of those genes, rather weak signals of transcription factor binding sites...

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Incorporating Nucleosome Occupancy to Predict Transcription Factor Binding Sites

Bo Jiang April 29, 2007 ABSTRACT Traditional methods to identify potential binding sites of known transcription factors usually neglect abundant information hidden in a large genomic scale. Recent researches, however, reveal that the intrinsic nucleosome organization in genome can be predicted and may help in directing transcription factors towards their target sites. In this paper, we present ...

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Positional distribution of human transcription factor binding sites

We developed a method for estimating the positional distribution of transcription factor (TF) binding sites using ChIP-chip data, and applied it to recently published experiments on binding sites of nine TFs: OCT4, SOX2, NANOG, HNF1A, HNF4A, HNF6, FOXA2, USF1 and CREB1. The data were obtained from a genome-wide coverage of promoter regions from 8-kb upstream of the transcription start site (TSS...

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Positional distribution of transcription factor binding sites in Arabidopsis thaliana.

Binding of a transcription factor (TF) to its DNA binding sites (TFBSs) is a critical step to initiate the transcription of its target genes. It is therefore interesting to know where the TFBSs of a gene are likely to locate in the promoter region. Here we studied the positional distribution of TFBSs in Arabidopsis thaliana, for which many known TFBSs are now available. We developed a method to...

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Information Content in Transcription Factor Binding Sites

The application of Information Theory to the analysis of genomic sequences and, specifically, transcription factor binding sites, is one of the most successful attempts at modeling the behavior and evolution of these genomic elements. As such, information theory models lie at the core of many transcription factor binding site search and motif discovery tools, such as the widely used Virtual Foo...

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ژورنال

عنوان ژورنال: Bioinformatics

سال: 2001

ISSN: 1367-4803,1460-2059

DOI: 10.1093/bioinformatics/17.11.1019