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The Sequence Alignment and Modeling system (SAM) is a collection of flexible software tools for creating, refining, and using linear hidden Markov models for biological sequence analysis. The model states can be viewed as representing the sequence of columns in a multiple sequence alignment, with provisions for arbitrary position-dependent insertions and deletions in each sequence. The models are trained on a family of protein or nucleic acid sequences using an expectation-maximization algorithm and a variety of algorithmic heuristics. A trained model can then be used to both generate multiple alignments and search databases for new members of the family. SAM is written in the C programming language for Unix machines and MasPar parallel computers, and includes extensive documentation. The algorithms and methods used by SAM have been described in several pioneering papers from the University of California, Santa Cruz. These papers, as well as the SAM software suite, are available via anonymous ftp to ftp.cse.ucsc.edu in the pub/protein directory, or via the World-Wide Web to http://www.cse.ucsc.edu/research/compbio/.