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Molecular biologists use hidden Markov models (HMMs) as a popular tool to statistically describe biological sequence families. This statistical description can then be used for sensitive and selective database scanning, e.g., new protein sequences are compared with a set of HMMs to detect functional similarities. Efficient dynamic-programming algorithms exist for solving this problem; however, current...
In this paper, we present a technique to optimize the performance of database similarity search in the specific context of Cell Broadband Engine Architecture (CBEA). The technique applied was Striped Smith-Waterman algorithm for SIMD and heterogeneous task distribution in MIMD.In terms of sensitivity, the technique preserves the optimality of original Smith- Waterman algorithm. In addition, the performance...
Profile hidden Markov models (profile HMMs) are used as a popular bioinformatics tool for sensitive database searching, e.g. a set of not annotated protein sequences is compared to a database of profile HMMs to detect functional similarities. HMMer is a commonly used package for profile HMM-based methods. However, searching large databases with HMMer suffers from long runtimes on traditional computer...
Sequence alignment is a common and often repeated task in molecular biology. The need for speeding up this treatment comes from the rapid growth rate of biological sequence databases. In this paper we present a new approach to high performance biological sequence database scanning on graphics processing units. Using modern graphics processing units for high performance computing is facilitated by...
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