The General Hidden Markov Model library (GHMM) is a freely available LGPL-ed C library implementing efficient data structures and algorithms for basic and extended HMMs. The development is hosted at Sourceforge http://sourceforge.net/projects/ghmm/, where you have access to the Subversion repository, mailing lists and forums.
HMMEd (the Hidden Markov Model editor) is a graphical application which allows to create and edit Hidden Markov Models. Supported are
Discrete emission probabilities, as well as transition probabilities can be graphically edited using pie charts with handles. Parameters can also be entered directly. HMM topology can be edited manually by adding/deleting states and connecting them with the mouse. Hierarchical models, i.e. super nodes corresponding to complete promoters or codon models in gene finding HMMs, will be supported. Currently, a visually pleasant layout has to be done by hand.
For models with continous emission, a graphical editor for mixtures of pdfs is under development. A screenshot from a working prototype is shown above. The handles underneath the pdfs change mean as well as other pdf parameters, the pie chart controls the mixture coefficients.
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Knab, Bernhard. Extension of Hidden Markov Models for the analysis of financial time-series data (2000) [details]
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Schliep, Alexander and Costa, Ivan G. and Steinhoff, Christine and Schönhuth, Alexander. Analyzing gene expression time-courses (2005) [details]
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Schönhuth, Alexander and Costa, Ivan G. and Schliep, Alexander. Semi-supervised Clustering of Yeast Gene Expression (2009) [details]
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