Aligning Multiple Biosequences Progressively on Cluster Grids using ALiCE

摘要: In the absence of powerful supercomputer hardware, grid computing offers an alternative avenue by providing a heterogeneous, scalable and reliable high performance processing environment to address problems involving large computational granularities enormous datasets. The physical life sciences typically include numerous classes sophisticated retrieval information from volumes formatted databases. This paper reports development deployment bioinformatics problem, Progressive Multiple Sequence Alignment (PMSA), on cluster grids using ALiCE, middleware. PMSA comprises three consecutive stages: pairwise sequence comparison, guide tree construction profiles alignment. Our implementation involves parallelizing first third stages algorithm. Experiments homogeneous heterogeneous demonstrate how scales with problem size power, illustrating that is feasible means approach several categories in integrating pooled resources produce supercomputing capabilities.