Journal Article

Evolutionary construction of multiple graph alignments for the structural analysis of biomolecules

Thomas Fober, Marco Mernberger, Gerhard Klebe and Eyke Hüllermeier

in Bioinformatics

Volume 25, issue 16, pages 2110-2117
Published in print August 2009 | ISSN: 1367-4803
Published online March 2009 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btp144
Evolutionary construction of multiple graph alignments for the structural analysis of biomolecules

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The concept of multiple graph alignment (MGA) has recently been introduced as a novel method for the structural analysis of biomolecules. Using approximate graph matching techniques, this method enables the robust identification of approximately conserved patterns in biologically related structures. In particular, MGA enables the characterization of functional protein families independent of sequence or fold homology. This article first recalls the concept of MGA and then addresses the problem of computing optimal alignments from an algorithmic point of view. In this regard, a method from the field of evolutionary algorithms is proposed and empirically compared with a hitherto existing heuristic approach. Empirically, it is shown that the former yields significantly better results than the latter, albeit at the cost of an increased runtime.

Contact: eyke@mathematik.uni-marburg.de

Supplementary information: Supplementary data are available at Bioinformatics online.

Journal Article.  6198 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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