Abstract
The growing amount of biological data, including macromolecular data describing 3D protein structures, encourages the scientific community to reach for computing resources of the Cloud in order to process and analyze the data on a large scale. This applies, among many different analytical processes performed in bioinformatics, to protein structure alignment and similarity searching. In this paper, we show a parameter sweep-based approach for scheduling computations related to massive 3D protein structure alignments performed with Cloud4PSi system working on Microsoft Azure public cloud.
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Acknowledgments
This work was supported by The National Centre for Research and Development grant No. PBS3/B3/32/2015 and by Microsoft Research within Microsoft Azure for Research grant.
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Mrozek, D., Kłapciński, A., Małysiak-Mrozek, B. (2017). Orchestrating Task Execution in Cloud4PSi for Scalable Processing of Macromolecular Data of 3D Protein Structures. In: Nguyen, N., Tojo, S., Nguyen, L., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2017. Lecture Notes in Computer Science(), vol 10192. Springer, Cham. https://doi.org/10.1007/978-3-319-54430-4_69
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DOI: https://doi.org/10.1007/978-3-319-54430-4_69
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