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: StochHMM is implemented in C++ and is available under the MIT License. Software, source code, documentation, and examples can be found at