SciPhy: a cloud-based workflow for phylogenetic analysis of drug targets in protozoan genomes

Authors:
Kary A. C. S. Ocaña;Daniel de Oliveira;Eduardo Ogasawara;Alberto M. R. Dávila;Alexandre A. B. Lima;Marta Mattoso
Affiliations:
Computer Science, COPPE, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil;Computer Science, COPPE, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil;Computer Science, COPPE, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil and Federal Center of Technological Education, Rio de Janeiro, Brazil;Laboratory of Computational and Systems Biology, IOC, FIOCRUZ, Rio de Janeiro, Brazil;Computer Science, COPPE, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil;Computer Science, COPPE, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
Venue:
BSB'11 Proceedings of the 6th Brazilian conference on Advances in bioinformatics and computational biology
Year:
2011

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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.