Context-specific independence mixture modeling for positional weight matrices
نویسندگان
چکیده
منابع مشابه
Context-specific independence mixture modeling for positional weight matrices
MOTIVATION A positional weight matrix (PWM) is a statistical representation of the binding pattern of a transcription factor estimated from known binding site sequences. Previous studies showed that for factors which bind to divergent binding sites, mixtures of multiple PWMs increase performance. However, estimating a conventional mixture distribution for each position will in many cases cause ...
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MOTIVATION Positional weight matrix (PWM) is derived from a set of experimentally determined binding sites. Here we explore whether there exist subclasses of binding sites and if the mixture of these subclass-PWMs can improve the binding site prediction. Intuitively, the subclasses correspond to either distinct binding preference of the same transcription factor in different contexts or distinc...
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Bayesiannetworks provide a languagefor qualitatively representing the conditional independence properties of a distribution. This allows a natural and compact representation of the distribution, eases knowledge acquisition, and supports effective inference algorithms. It is well-known, however, that there are certain independencies that we cannot capture qualitatively within the Bayesian networ...
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ژورنال
عنوان ژورنال: Bioinformatics
سال: 2006
ISSN: 1367-4803,1460-2059
DOI: 10.1093/bioinformatics/btl249