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mCarts

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A hidden Markov model to predict clustered RNA motif sites

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Description

Many RBPs recognize very short and degenerate sequences, with targeting specificity achieved by mechanisms such as synergistic binding to multiple clustered sites and modulation of site accessibility through different RNA-secondary structures. mCarts integrates the number and spacing of individual motif sites, their accessibility and conservation, which substantially improves signal to noise ratio. This algorithm learns and quantifies rules of these features, taking advantage of a large number of in vivo RBP binding sites obtained from high throughput sequencing of RNAs isolated by cross-linking and immunoprecipitation (HITS-CLIP). We applied this algorithm to study two representative RBPs, Nova and Mbnl. Despite the very low information content in individual motif elements, our algorithm made very specific predictions for successful experimental validation.

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Additional Project Details

Intended Audience

Science/Research, Advanced End Users

User Interface

Command-line

Programming Language

Perl

Registered

2012-09-20

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