Abstract
Finding similarities between protein structures is a crucial task in molecular biology. Many tools exist for finding an optimal alignment between two proteins. These tools, however, only find 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 fine- and coarse-grain parallelism.
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Streaming SIMD Extensions.
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Chapuis, G., Le Boudic - Jamin, M., Andonov, R., Djidjev, H., Lavenier, D. (2014). Parallel Seed-Based Approach to Protein Structure Similarity Detection. In: Wyrzykowski, R., Dongarra, J., Karczewski, K., Waśniewski, J. (eds) Parallel Processing and Applied Mathematics. PPAM 2013. Lecture Notes in Computer Science(), vol 8385. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55195-6_26
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DOI: https://doi.org/10.1007/978-3-642-55195-6_26
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