Abstract
Scalable parallel computer architectures provide the computational performance needed for advanced computing problems in molecular biology. Many scientific challenges in molecular biology have associated with them a computational requirement that must be solved before scientific progress can be made. We have developed a number of parallel algorithms and techniques useful in determining biological structure and function. Two example applications are the alignment of multiple DNA and protein sequences using speculative computation and the calculation of the solvent accessible surface area of proteins used to predict the three-dimensional conformation of these molecules from their primary structure. Timing results demonstrate substantial performance improvements with parallel implementations compared with conventional sequential systems. As the developed methods allow molecular biologists to perform computational tasks that would not otherwise be possible, we continue to develop parallel algorithms useful to this important scientific field.
Keywords
- Parallel Computing
- Parallel Algorithm
- Speedup Factor
- Solvent Accessible Surface Area
- Pairwise Sequence Alignment
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 1997 Springer-Verlag Berlin Heidelberg
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Martino, R.L., Yap, T.K., Suh, E.B. (1997). Parallel algorithms in molecular biology. In: Hertzberger, B., Sloot, P. (eds) High-Performance Computing and Networking. HPCN-Europe 1997. Lecture Notes in Computer Science, vol 1225. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0031596
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DOI: https://doi.org/10.1007/BFb0031596
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