Parallel seed-based approach to protein structure similarity detection

Guillaume Chapuis 1, * Mathilde Le Boudic-Jamin 1 Rumen Andonov 1 Hristo Djidjev 2 Dominique Lavenier 1
* Corresponding author
1 GenScale - Scalable, Optimized and Parallel Algorithms for Genomics
Inria Rennes – Bretagne Atlantique , IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
Abstract : Finding similarities between protein structures is a crucial task in molecular biology. Many tools exist for fi nding an optimal alignment between two proteins. These tools, however, only fi nd one alignment even when multiple similar regions exist. We propose a new parallel heuristic-based approach to structural similarity detection between proteins that discovers multiple pairs of similar regions. We prove that returned alignments have RMSDc and RMSDd lower than a given threshold. Computational complexity is addressed by taking advantage of both fi ne- and coarse-grain paralellism.
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https://hal.inria.fr/hal-00881507
Contributor : Guillaume Chapuis <>
Submitted on : Monday, November 18, 2013 - 3:53:56 PM
Last modification on : Thursday, November 15, 2018 - 11:57:53 AM
Long-term archiving on : Wednesday, February 19, 2014 - 4:32:08 AM

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Guillaume Chapuis, Mathilde Le Boudic-Jamin, Rumen Andonov, Hristo Djidjev, Dominique Lavenier. Parallel seed-based approach to protein structure similarity detection. PPAM 2013, Roman Wyrzykowski, Sep 2013, Varsovie, Poland. ⟨hal-00881507⟩

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