Abstract
Bioinformatics experiments are rapidly evolving with genomic projects that analyze large amounts of data. This fact demands high performance computation and opens up for exploring new approaches to provide better control and performance when running experiments, including Phylogeny/Phylogenomics. We designed a phylogenetic scientific workflow, named SciPhy, to construct phylogenetic trees from a set of drug target enzymes found in protozoan genomes. Our contribution is the development, implementation and test of SciPhy in public cloud computing environments. SciPhy can be used in other Bioinformatics experiments to control a systematic execution with high performance while producing provenance data.
This work was partially sponsored by CAPES, FAPERJ and CNPq.
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Ocaña, K.A.C.S., de Oliveira, D., Ogasawara, E., Dávila, A.M.R., Lima, A.A.B., Mattoso, M. (2011). SciPhy: A Cloud-Based Workflow for Phylogenetic Analysis of Drug Targets in Protozoan Genomes. In: Norberto de Souza, O., Telles, G.P., Palakal, M. (eds) Advances in Bioinformatics and Computational Biology. BSB 2011. Lecture Notes in Computer Science(), vol 6832. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22825-4_9
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DOI: https://doi.org/10.1007/978-3-642-22825-4_9
Publisher Name: Springer, Berlin, Heidelberg
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