dc.contributor.authorHe, Lu
dc.contributor.authorVandin, Fabio
dc.contributor.authorPandurangan, Gopal
dc.contributor.authorBailey-Kellogg, Chris
dc.date.accessioned2014-10-10T04:17:15Z
dc.date.available2014-10-10T04:17:15Z
dc.date.copyright2013en_US
dc.date.issued2013
dc.identifier.citationHe, L., Vandin, F., Pandurangan, G., & Bailey-Kellogg, C. (2013). Ballast : a ball-based algorithm for structural motifs. Journal of computational biology, 20(2), 137-151.en_US
dc.identifier.issn1066-5277en_US
dc.identifier.urihttp://hdl.handle.net/10220/23983
dc.description.abstractStructural motifs encapsulate local sequence-structure-function relationships characteristic of related proteins, enabling the prediction of functional characteristics of new proteins, providing molecular-level insights into how those functions are performed, and supporting the development of variants specifically maintaining or perturbing function in concert with other properties. Numerous computational methods have been developed to search through databases of structures for instances of specified motifs. However, it remains an open problem how best to leverage the local geometric and chemical constraints underlying structural motifs in order to develop motif-finding algorithms that are both theoretically and practically efficient. We present a simple, general, efficient approach, called Ballast (ball-based algorithm for structural motifs), to match given structural motifs to given structures. Ballast combines the best properties of previously developed methods, exploiting the composition and local geometry of a structural motif and its possible instances in order to effectively filter candidate matches. We show that on a wide range of motif-matching problems, Ballast efficiently and effectively finds good matches, and we provide theoretical insights into why it works well. By supporting generic measures of compositional and geometric similarity, Ballast provides a powerful substrate for the development of motif-matching algorithms.en_US
dc.format.extent15 p.en_US
dc.language.isoenen_US
dc.relation.ispartofseriesJournal of computational biologyen_US
dc.rights© 2013 Mary Ann Liebert. This paper was published in Journal of Computational Biology and is made available as an electronic reprint (preprint) with permission of Mary Ann Liebert. The paper can be found at the following official DOI: [http://dx.doi.org/10.1089/cmb.2012.0246]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.en_US
dc.subjectDRNTU::Engineering::Computer science and engineering::Theory of computation
dc.titleBallast : a ball-based algorithm for structural motifsen_US
dc.typeJournal Article
dc.contributor.schoolSchool of Physical and Mathematical Sciencesen_US
dc.identifier.doihttp://dx.doi.org/10.1089/cmb.2012.0246
dc.description.versionPublished versionen_US


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