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Githup repo: https://github.com/ayoshiaki/tops
ToPS is an objected-oriented framework implemented using C++ that facilitates the integration of probabilistic models for sequences over a user defined alphabet. ToPS contains the implementation of eight type of models to analyze discrete sequences:
Independent and identically distributed model
Variable-Length Markov Chain (VLMC)
Inhomogeneous Markov Chain
Hidden Markov Model
Pair Hidden Markov Model
Profile Hidden Markov Model
Similarity Based Sequence Weighting
Generalized Hidden Markov Model (GHMM)
The user can implement models either by manual description of the probability values in a configuration file, or by using training algorithms provided by the system. The ToPS framework also includes a set of programs that implement bayesian classifiers, sequence samplers, and sequence decoders. Finally, ToPS is an extensible and portable system that facilitates the implementation of other probabilistic models, and the development of new programs.