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Reconfigurable systems for the zuker and predator algorithms for secondary structure prediction of genetic data

Smerdis Miltiadis, Dagritzikos Panagiotis, Chrysos Grigorios, Sotiriadis Evripidis, Dollas Apostolos

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URIhttp://purl.tuc.gr/dl/dias/36EE0D4C-3E88-4BA2-8D6A-56F23845C2A7-
Identifierhttps://doi.org/10.1109/FPL.2010.91-
Identifierhttp://ieeexplore.ieee.org/document/5694292/-
Languageen-
Extent4 pagesen
TitleReconfigurable systems for the zuker and predator algorithms for secondary structure prediction of genetic dataen
CreatorSmerdis Miltiadisen
CreatorΣμερδης Μιλτιαδηςel
CreatorDagritzikos Panagiotisen
CreatorChrysos Grigoriosen
CreatorΧρυσος Γρηγοριοςel
CreatorSotiriadis Evripidisen
CreatorΣωτηριαδης Ευριπιδηςel
CreatorDollas Apostolosen
CreatorΔολλας Αποστολοςel
PublisherInstitute of Electrical and Electronics Engineersen
Content SummarySecondary structure prediction is a compute-intensive task that is used in many bioinformatics applications. In this paper we have selected two of the most well-known secondary structure prediction algorithms, the Predator and the Zuker algorithm, and we present two FPGA-based systems that implement them. Also, this paper presents different schemes of data reuse and data organization of structure prediction systems to avoid the data I/O bottleneck. The speedup of the execution time is at least 37x for the Predator method and 3x for the Zuker method compared to the corresponding software implementations. Finally, this paper shows that the exploitation of FPGA capabilities offers high performance systems that can be used by the bioinformatics community.en
Type of ItemΔημοσίευση σε Συνέδριοel
Type of ItemConference Publicationen
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-11-17-
Date of Publication2010-
SubjectInformaticsen
Subjectcomputer scienceen
Subjectinformaticsen
Bibliographic CitationM. Smerdis, P. Dagritzikos, G. Chrysos, E. Sotiriades and A. Dollas, "Reconfigurable systems for the Zuker and Predator algorithms for secondary structure prediction of genetic data," in International Conference on Field Programmable Logic and Applications, 2010, pp. 448-451. doi: 10.1109/FPL.2010.91en

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