ProfNet, a method to derive profile-profile alignment scoring functions that improves the alignments of distantly related protei

Background: Profile-profile methods have been used for some years now to detect and align homologous proteins. The best such methods use information from the background distribution of amino acids and substitution tables either when constructing the profiles or in the scoring. This makes the methods dependent on the quality and choice of substitution table as well as the construction of the profiles. Here, we introduce a novel method called ProfNet that is used to derive a profile-profile scoring function. The method optimizes the discrimination between scores of related and unrelated residues and it is fast and straightforward to use. This new method derives a scoring function that is mainly dependent on the actual alignment of residues from a training set, and it does not use any additional information about the background distribution. Results: It is shown that ProfNet improves the discrimination of related and unrelated residues. Further it can be used to improve the alignment of ...

• Type: Journal
• Year: 2005
• Where: BMCBI
• Authors: Tomas Ohlson, Arne Elofsson
• Keywords: BMCBI 2005, Profile-profile Scoring Function, Scoring Function, Substitution Table