Occupancy Classification of Position Weight Matrix-Inferred Transcription Factor Binding Sites

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Occupancy Classification of Position Weight Matrix-Inferred Transcription Factor Binding Sites

BACKGROUND Computational prediction of Transcription Factor Binding Sites (TFBS) from sequence data alone is difficult and error-prone. Machine learning techniques utilizing additional environmental information about a predicted binding site (such as distances from the site to particular chromatin features) to determine its occupancy/functionality class show promise as methods to achieve more a...

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Dinucleotide Weight Matrices for Predicting Transcription Factor Binding Sites: Generalizing the Position Weight Matrix

BACKGROUND Identifying transcription factor binding sites (TFBS) in silico is key in understanding gene regulation. TFBS are string patterns that exhibit some variability, commonly modelled as "position weight matrices" (PWMs). Though convenient, the PWM has significant limitations, in particular the assumed independence of positions within the binding motif; and predictions based on PWMs are u...

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Transcription Factor Binding Sites: Position-Specific and Position-Dependent Modeling

Transcription of a gene is cued by the binding of a protein to a binding site. Transcription factors bind to specific binding sites (TFBSs), of which there may be many for a single transcription factor (1). However, these TFBSs often exhibit a considerable amount of variability, as the sequences consist of similar nucleotides rather than complete replicas of a TFBS (1). The ability to model the...

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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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Similarity of position frequency matrices for transcription factor binding sites

MOTIVATION Transcription-factor binding sites (TFBS) in promoter sequences of higher eukaryotes are commonly modeled using position frequency matrices (PFM). The ability to compare PFMs representing binding sites is especially important for de novo sequence motif discovery, where it is desirable to compare putative matrices to one another and to known matrices. RESULTS We describe a PFM simil...

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ژورنال

عنوان ژورنال: PLoS ONE

سال: 2011

ISSN: 1932-6203

DOI: 10.1371/journal.pone.0026160