Comparative homology agreement search: An effective combination of homology-search methods

Intikhab Alam, Andreas Dress, Marc Rehmsmeier, Georg Fuellen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Many methods have been developed to search for homologous members of a protein family in databases, and the reliability of results and conclusions may be compromised if only one method is used, neglecting the others. Here we introduce a general scheme for combining such methods. Based on this scheme, we implemented a tool called comparative homology agreement search (CHASE) that integrates different search strategies to obtain a combined "E value." Our results show that a consensus method integrating distinct strategies easily outperforms any of its component algorithms. More specifically, an evaluation based on the Structural Classification of Proteins database reveals that, on average, a coverage of 47% can be obtained in searches for distantly related homologues (i.e., members of the same superfamily but not the same family, which is a very difficult task), accepting only 10 false positives, whereas the individual methods obtain a coverage of 28-38%.

Original languageEnglish (US)
Pages (from-to)13814-13819
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Volume101
Issue number38
DOIs
StatePublished - Sep 21 2004

ASJC Scopus subject areas

  • General

Fingerprint Dive into the research topics of 'Comparative homology agreement search: An effective combination of homology-search methods'. Together they form a unique fingerprint.

Cite this