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A Scalable Grid Computing Framework for Extensible Phylogenetic Profile Construction

Abstract : Current research in Life Sciences without doubt has been established as a Big Data discipline. Beyond the expected domain-specific requirements, this perspective has put scalability as one of the most crucial aspects of any state-of-the-art bioinformatics framework. Sequence alignment and construction of phylogenetic profiles are common tasks evident in a wide range of life science analyses as, given an arbitrary big volume of genomes, they can provide useful insights on the functionality and relationships of the involved entities. This process is often a computational bottleneck in existing solutions, due to its inherent complexity. Our proposed distributed framework manages to perform both tasks with significant speed-up by employing Grid Computing resources provided by EGI in an efficient and optimal manner. The overall workflow is both fully automated, thus making it user friendly, and fully detached from the end-users terminal, since all computations take place on Grid worker nodes.
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Emmanouil Stergiadis, Athanassios M. Kintsakis, Fotis E. Psomopoulos, Pericles A. Mitkas. A Scalable Grid Computing Framework for Extensible Phylogenetic Profile Construction. 12th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2016, Thessaloniki, Greece. pp.455-462, ⟨10.1007/978-3-319-44944-9_39⟩. ⟨hal-01557618⟩



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