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kmerHMM

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

Natasha

Excellent Tool for Multiple Motifs Disocovery

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kmerHMM classification

kmerHMM specifications

Software type:
Package/Module
Restrictions to use:
None
Programming languages:
MATLAB
Stability:
Stable
Interface:
Command line interface
Operating system:
Unix/Linux, Mac OS, Windows
Computer skills:
Advanced
Maintained:
Yes

kmerHMM distribution

versioning

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No versioning.

Credits

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Publications

Institution(s)

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

Link to literature

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