General Information
| Description | A flexible hidden Markov model tool and C++ library |
| Homepage | http://github.com/KorfLab/StochHMM |
Publications
StochHMM: a flexible hidden Markov model tool and C++ library
Summary:
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.
Availability and implementation:
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.
Contact:
ifkorf@ucdavis.edu
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