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Bioinformatics Advance Access originally published online on May 5, 2007
Bioinformatics 2007 23(14):1834-1836; doi:10.1093/bioinformatics/btm240
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© The Author 2007. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Automated Improvement of Domain ANnotations using context analysis of domain arrangements (AIDAN)

Francois Beaussart , January Weiner, 3rd and Erich Bornberg-Bauer *

Evolutionary Bioinformatics, Institute for Evolution and Biodiversity, Westfälische Wilhelms University, Schlossplatz 4, D48149 Münster, Germany

*To whom correspondence should be addressed.


  Abstract

Motivation: Since protein domains are the units of evolution, databases of domain signatures such as ProDom or Pfam enable both a sensitive and selective sequence analysis. However, manually curated databases have a low coverage and automatically generated ones often miss relationships which have not yet been discovered between domains or cannot display similarities between domains which have drifted apart.

Methods: We present a tool which makes use of the fact that overall domain arrangements are often conserved. AIDAN (Automated Improvement of Domain ANnotations) identifies potential annotation artifacts and domains which have drifted apart. The underlying database supplements ProDom and is interfaced by a graphical tool allowing the localization of single domain deletions or annotations which have been falsely made by the automated procedure.

Availability: http://www.uni-muenster.de/Evolution/ebb/Services/AIDAN

Contact: ebb{at}uni-muenster.de

Supplementary information: Supplementary data are available at Bioinformatics online.

Associate Editor: Dmitrij Frishman

Received on December 8, 2006; revised on April 18, 2007; accepted on April 27, 2007

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K. Forslund and E. L. L. Sonnhammer
Predicting protein function from domain content
Bioinformatics, August 1, 2008; 24(15): 1681 - 1687.
[Abstract] [Full Text] [PDF]


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