A Peer-to-Peer system for executing bioinformatics applications: a case study of distributed and scalable information management over massive volumes of data - Ribeiro, E. O.; Walter, M. E. M. T.; Costa, M. M.; Pappas, G.; Network, BIOFOCO (Anais do Seminário Integrado de Software e Hardware (SEMISH), 2008)
The enourmous and heterogeneous data sets, distributed on the world, that must be processed in order to extract useful information, generated research in new techniques and methods for processing them correctly and in an acceptable time. Particularly, bioinformatics applications require large amounts of computational resources, as the algorithms are time expensive and the databases are heterogeneous and space consuming. Besides, the Peer-to-Peer (P2P) model has been successfully used for applications demanding great amount of computational resources that are executed on geographically distributed machines. So, in this work, we propose a distributed environment using the P2P model that can execute bioinformatics applications. For testing the system, we used BLAST, a family of algorithms for searching similarities between two biological sequences, since it is broadly used and requires a great amount of computation, due to very large databases. We describe the architecture of our framework, and present experiments using real biological data, that were executed on machines of three institutions, University of Brasilia, Catholic University of Brasilia and Embrapa/Genetic Resources and Biotechnology. The good results achieved, when comparing the performance of our distributed system with a standalone BLAST execution, show that P2P model can be successfully applied to bioinformatics applications. Generically, our system could contribute, in practice, for processing applications demanding massive volumes of data. At last, we address how our work relates with the Grand Challenges in Computer Science Research in Brazil (2006− 2016), as proposed by the Brazilian Computer Society, and discuss some research trends related to these Challenges.