Dinucleotide Weight Matrices for Predicting Transcription Factor Binding Sites: Generalizing the Position Weight Matrix
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منابع مشابه
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...
متن کاملIdentification of co-occurring transcription factor binding sites from DNA sequence using clustered position weight matrices
Accurate prediction of transcription factor binding sites (TFBSs) is a prerequisite for identifying cis-regulatory modules that underlie transcriptional regulatory circuits encoded in the genome. Here, we present a computational framework for detecting TFBSs, when multiple position weight matrices (PWMs) for a transcription factor are available. Grouping multiple PWMs of a transcription factor ...
متن کاملOccupancy 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...
متن کاملSimilarity 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...
متن کاملMORPHEUS, a Webtool for Transcription Factor Binding Analysis Using Position Weight Matrices with Dependency
Transcriptional networks are central to any biological process and changes affecting transcription factors or their binding sites in the genome are a key factor driving evolution. As more organisms are being sequenced, tools are needed to easily predict transcription factor binding sites (TFBS) presence and affinity from mere inspection of genomic sequences. Although many TFBS discovery algorit...
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ژورنال
عنوان ژورنال: PLoS ONE
سال: 2010
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0009722