The General Hidden Markov Model library (GHMM) is a freely available C library implementing efficient data structures and algorithms for basic and extended HMMs with discrete and …

The best sources are a standard text on HMM such as Rabiner's Tutorial on Hidden Markov Models to understand the theory, the publications using the GHMM and the help information, …

This stochastic process we will model with a HMM. Below > is your shell prompt and >>> is the prompt of the Python interpreter and you should type whatever follows the prompt omitting the …

HMMEd: the HMM Editor GQL Pair HMMs Publications Contributors MPI Molecular Genetics. Developers: Alexander Schliep Benjamin Georgi Wasinee Rungsarityotin Ivan G. Costa Janne …

Linux: various distributions are creative about install locations and the scope of what actually is installed. You want the developer/header whatever-they-are-called packages in addition to …

HMMs are stochastic models which encode a probability density over sequences of symbols. These symbols can be discrete letters (A,C,G and T for DNA; 1,2,3,4,5,6 for dice), real …

The General Hidden Markov Model library (GHMM) has been used for published research papers and theses: Michael Seifert Analyzing Microarray Data Using Homogenous and …

Robust inference of groups in gene expression time-courses using mixtures of HMM. Proceedings of the ISMB 2004. Bioinformatics, Aug 2004; 20 Suppl 1: I283 - I289.

The pair HMM is mainly specified by a graphML based XML file which can be partly created using the HMMEd. The emission probabilities and the alphabets have to be defined manually in the …

HMMEd: Hidden Markov Model editor. HMMEd (the Hidden Markov Model editor) is a graphical application which allows to create and edit Hidden Markov Models. Supported are discrete …