Sean Eddy's lab, present profile hidden Markov models for biological sequence analysis, a tool used to build HMMs from multiple alignments, and calculate e-scores. http://hmmer.wustl.edu/
Software toolkit for building and using motif-based hidden Markov models of DNA and proteins - from the Univ. of California-San Diego. http://metameme.sdsc.edu/
Suite that implements decision trees and tables, rule learners, Naive Bayes, support vector machines, voted perceptrons, multi-layer perceptron. Meta schemes include bagging, stacking, and boosting. [Free under GPL] http://www.cs.waikato.ac.nz/~ml/weka/index.html
A software package developed at MIT Lincoln Laboratory which integrates more than 20 neural network, statistical, and machine learning classification, clustering, and feature selection algorithms into a modular software package. [Public domain license] http://www.ll.mit.edu/IST/lnknet/index.html
A library of C code useful for writing statistical text analysis, language modeling and information retrieval programs. The current distribution includes the library, as well as front-ends for document classification (rainbow), document retrieval (arrow) http://www.cs.cmu.edu/~mccallum/bow/
MEME System is a program for discovering motifs in groups of related DNA or protein sequences. MAST is a tool for searching biological sequence databases for sequences that contain one or more of a group of known motifs. http://meme.sdsc.edu/meme/website/
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