- Unique identifier:
- Command line interface
- Input data:
- A Protein Binding Mircoarray (PBM) probe intensity file.
- Operating system:
- Unix/Linux, Mac OS, Windows
- Computer skills:
- Software type:
- Restrictions to use:
- Output data:
- A Hidden Markov Model (HMM) motif model and the most probable path motif logo.
- Programming languages:
No open topic.
(Wong et al., 2013)
DNA motif elucidation using belief propagation.
Nucleic Acids Res.
PMID: 23814189 DOI: 10.1093/nar/gkt574
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
Supported by Discovery Grant from Natural Sciences and Engineering Research Council, Canada (NSERC), grant number [327612-2009 RGPIN]; Acres Inc. – Joseph Yonan Memorial Fellowship, Kwok Sau Po Scholarship, and International Research and Teaching Assistantship from University of Toronto; Cofunded by NSERC Canada Graduate Scholarship and Ontario Graduate Scholarship.
2 user reviews
2 user reviews
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).
Excellent Tool for Multiple Motifs Disocovery