Article
SparkBLAST: scalable BLAST processing using in-memory operations
Registro en:
CASTRO, Marcelo Rodrigo de; et al. SparkBLAST: scalable BLAST processing using in-memory operations. BMC Bioinformatics, v.18:318, 13p, 2017.
1471-2105
10.1186/s12859-017-1723-8
Autor
Castro, Marcelo Rodrigo de
Tostes, Catherine dos Santos
Dávila, Alberto M. R.
Senger, Hermes
Silva, Fabricio A. B. da
Resumen
The demand for processing ever increasing amounts of genomic data has raised new challenges for the implementation of highly scalable and efficient computational systems. In this paper we propose SparkBLAST, a parallelization of a sequence alignment application (BLAST) that employs cloud computing for the provisioning of computational resources and Apache Spark as the coordination framework. As a proof of concept, some radionuclide-resistant bacterial genomes were selected for similarity analysis.