StochHMM: a flexible hidden Markov model tool and C++ library.
Hidden Markov models (HMMs) are probabilistic models that are well-suited to solve many different classification problems in computation biology. StochHMM provides a command-line program and C++ library that can implement a traditional HMM from a simple text file. StochHMM provides researchers the flexibility to create higher-order emissions, integrate additional data sources and/or user-defined functions into multiple points within the HMM framework. Additional features include user-defined alphabets, ability to handle ambiguous characters in an emission-dependent manner, user-defined weighting of state paths and ability to tie transition probabilities to sequence.


METHODS
StochHMM is implemented in C++ and is available under the MIT License. Software, source code, documentation and examples can be found at http://github.com/KorfLab/StochHMM.
Genome Center, One Shields Ave., University of California, Davis, CA 95616, USA.
Paul C
PC
Lott
Genome Center, One Shields Ave., University of California, Davis, CA 95616, USA.
Ian
I
Korf
D000465:Algorithms; D008390:Markov Chains; D015233:Models, Statistical; D017421:Sequence Analysis / Q000379:methods*; D012984:Software