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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 includes programs and scripts for the SAM-T99 method of remote homology detection. SAM-T99 is an iterative HMM search method for creating an HMM from a single protein sequence or seed alignment using iterative search of a protein database. The method is currently the most sensitive purely-sequence-based remote homology detection algorithm. SAM-T99 is based on successful methods created for the CASP2 and CASP3 protein structure prediction experiments.