MOTIVATION As databanks grow, sequence classification and prediction of function by searching protein family databases becomes increasingly valuable. The original Blocks Database, which contains ungapped multiple alignments for families documented in Prosite, can be searched to classify new sequences. However, Prosite is incomplete, and families from other databases are now available to expand ...

prosite database contains a set of entries corresponding to protein families, which are used to identify the family of a protein from its sequence. although patterns and profiles are developed to be very selective, each may have false positive or negative hits. considering false positives as items that reduce the selectiveness of a pattern, then, the more selective pattern we have, a more accur...

PROSITE (http://prosite.expasy.org/) consists of documentation entries describing protein domains, families and functional sites, as well as associated patterns and profiles to identify them. It is complemented by ProRule a collection of rules, which increases the discriminatory power of these profiles and patterns by providing additional information about functionally and/or structurally criti...

ProClass is a protein family database which organizes non-redundant sequence entries into families defined collectively by the ProSite patterns and PIR superfamilies. The database consists of about 100,000 entries, more than half of which are classified in about 3,000 families. The new version includes links to various protein family/domain and structural class databases and contains gapped mot...

PROSITE is a compilation of sites and patterns found in protein sequences. The use of protein sequence patterns (or motifs) to determine the function of proteins is becoming very rapidly one of the essential tools of sequence analysis. This reality has been recognized by many authors. While there have been a number of recent reports that review published patterns, no attempt had been made until...

The PROSITE database consists of biologically significant patterns and profiles formulated in such a way that with appropriate computational tools it can help to determine to which known family of proteins (if any) a new sequence belongs or which known domain(s) it contains.

We have extended the pattern language used in PROSITE to enable it to describe dependencies between amino acid residues. We have developed a minimum description length principle based tness measure evaluating the signiicance of such patterns in relation to a set of sequences, and an algorithm automatically nding signiicant patterns in unaligned sequences. Computing experiments are reported show...