StochHMM is a free, open source C++ Library and application that implements HMM from simple text files. It implements traditional HMM algorithms in addition it providing additional flexibility. The additional flexibility is achieved by allowing researchers to integrate additional data sources and application into the HMM framework.

C-HMM is a software to detect remote/distant homologues from protein sequence databases. It is based on HMMs (Hidden Markov Models) for identifying the deep evolutionary relationships of protein sequences.

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This is a C library for Hidden Markov Model (HMM). HMM with continuous observation space (Gaussian mixtures). Build system: For documentation: Like all CMake projects, to build and install, simply do: mkdir build. cd build. cmake .. make && make install. To make the documentation, do: make doc.

Hidden Markov models (HMMs) are a probability distribution over sequences that are made up of two components: a set of probability distributions and a transition matrix (sometimes represented as a graph) describing how sequences can proceed through the model.

The Cascade-Hidden Markov Model (C-HMM) involves cascading of HMM to identify the true distant homologues at various levels.

In this lecture, we dive more deeply into the capabilities of HMMs, focusing mostly on their use in evaluation. We discuss higher order HMMs, and end with a brief discussion of HMM learning, to be expanded on in the next lecture. The main example used to illustrate the concepts of HMMs is the idea of \CpG islands."

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2013年7月30日 · StochHMM is a free, open source C++ Library and application that implements HMM from simple text files. It implements traditional HMM algorithms in addition it providing additional flexibility. The additional flexibility is achieved by allowing researchers to integrate additional data sources and application into the HMM framework.