Selected Parallel Algorithms for Bioinformatics applications
Parallel Computing for Bioinformatics Applications
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DNA and protein databases have been increasing significantly over the last few years. The current tools which are based on sequential analysis and heuristics failed to cope with this increase. Consequently, there is a need to further reduce their running time. Parallel computing represented in its distributed and shared memory architectures is a solution to achieve scalable time reduction in sequence analysis. In parallel computing, the main problem is divided into sub-problems and each one is processed in parallel on a different physical processor to gain faster results. The continuous evolut...
DNA and protein databases have been increasing significantly over the last few years. The current tools which are based on sequential analysis and heuristics failed to cope with this increase. Consequently, there is a need to further reduce their running time. Parallel computing represented in its distributed and shared memory architectures is a solution to achieve scalable time reduction in sequence analysis. In parallel computing, the main problem is divided into sub-problems and each one is processed in parallel on a different physical processor to gain faster results. The continuous evolution in parallel computing technologies (multicore and distributed processors) made them widely manufactured and easily possessed. In this Book we focus on different parallel algorithms and tools that have been implemented and modified for sequence analysis, namely; WinBioinftools, Parallel Chaining algorithms, and Parallel Suffix array constructions. The developed and modified tools are implemented on distributed and shared memory architectures in different environments; Linux and Windows.
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