We are pleased to announce a WWW server for creating and using
linear hidden Markov models (HMMs) for sequence alignment and
In conjunction with this, we are releasing Version 1.1 of SAM,
the Sequence Alignment and Modeling Software Suite.
The WWW server comes in 2 flavors: a simple one (cut and
paste in the sequences, receive model, alignment, and score file
back) complex one, in which SAM's many parameters can be
Because constructing an HMM can be a time-consuming process,
results are emailed back to you rather than displayed as a web
page. The server will only process one request at a time, so
there may be a delay if a long request is currently running.
To get a copy of the code, which is free for non-commercial research
use, you will need to send email to sam-info at cse.ucsc.edu.
Go to: http://www.cse.ucsc.edu/research/compbio/sam.html
for pointers to the code and the forms-based WWW server, as well
as links to other UCSC compbio projects.
sam-info at cse.ucsc.edu
Richard Hughey (University of California, Santa Cruz)
Anders Krogh (Sanger Center, Cambridge)
Christian Barrett (University of California, Santa Cruz)
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
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 the
World-Wide Web to http://www.cse.ucsc.edu/research/compbio/sam.html.