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Motif Discovery on Protein Binding Microarray (PBM) data using Hidden Markov Model and Belief Propagation.

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2 user reviews

2 user reviews

Ka-Chun Wong's avatar image

Ka-Chun Wong

kmerHMM is designed for motif discovery on protein binding microarray (PBM) data. Especially, its multiple motif elucidation ability has been developed to such an extent that ad hoc processing is not needed by using Hidden Markov Model (HMM). I believe the software can be used on other data with sufficient modification. Especially, its methodology is very mature and novel (belief propagation and HMM).

Natasha's avatar image


Excellent Tool for Multiple Motifs Disocovery

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kmerHMM classification

kmerHMM specifications

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Command line interface
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Unix/Linux, Mac OS, Windows
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Department of Computer Science, University of Toronto, Toronto, ON, Canada; Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada; Department of Integrative Biology and Physiology, University of California Los Angeles, Los Angeles, CA, USA; Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Jeddah, Saudi Arabia; Banting and Best Department of Medical Research, University of Toronto, Toronto, ON, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada

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