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Graph theoretic methods for the analysis of structural relationships in biological macromolecules

Artymiuk, P.J., Spriggs, R.V. and Willett, P. (2005) Graph theoretic methods for the analysis of structural relationships in biological macromolecules. Journal of the American Society for Information Science and Technology, 56 (5). pp. 518-528. ISSN 1532 - 2882

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Abstract

Subgraph isomorphism and maximum common subgraph isomorphism algorithms from graph theory provide an effective and an efficient way of identifying structural relationships between biological macromolecules. They thus provide a natural complement to the pattern matching algorithms that are used in bioinformatics to identify sequence relationships. Examples are provided of the use of graph theory to analyze proteins for which three-dimensional crystallographic or NMR structures are available, focusing on the use of the Bron-Kerbosch clique detection algorithm to identify common folding motifs and of the Ullmann subgraph isomorphism algorithm to identify patterns of amino acid residues. Our methods are also applicable to other types of biological macromolecule, such as carbohydrate and nucleic acid structures.

Item Type: Article
Copyright, Publisher and Additional Information: © 2005 Wiley Periodicals, Inc. This is an author produced version of a paper published in Journal of the American Society for Information Science and Technology. Uploaded in accordance with the publisher's self-archiving policy.
Keywords: ASSAM, Carbohydrate structure, Complex Carbohydrate Structure Database, Database searching, Graph theory, Maximum common subgraph isomorphism, NASSAM, Nucleic acid structure, Protein Data Bank, Protein structure, PROTEP, RNA, Subgraph isomorphism, Substructure searching
Academic Units: The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield)
The University of Sheffield > University of Sheffield Research Centres and Institutes > The Krebs Institute for Biomolecular Research (Sheffield)
The University of Sheffield > Faculty of Science (Sheffield) > School of Biological Sciences (Sheffield) > Department of Molecular Biology and Biotechnology (Sheffield)
Depositing User: Sherpa Assistant
Date Deposited: 24 Jan 2008 17:08
Last Modified: 08 Feb 2013 16:55
Published Version: http://dx.doi.org/10.1002/asi.20140
Status: Published
Publisher: John Wiley & Sons, Inc.
Refereed: Yes
Identification Number: 10.1002/asi.20140
URI: http://eprints.whiterose.ac.uk/id/eprint/3591

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