Role of high performance parallel computing in biological research

Robert L. Martino; Calvin A. Johnson; Edward B. Suh; Benes L. Trus; Tieng K. Yap

Role of high performance parallel computing in biological research

Robert L. Martino, Calvin A. Johnson, Edward B. Suh, Benes L. Trus, Tieng K. Yap

Biostatistics

Research output: Contribution to journal › Conference article › peer-review

1 Scopus citations

Abstract

Scalable parallel computer architectures provide the computational performance demanded by advanced biological computing problems. NIH has developed a number of parallel algorithms and techniques useful in determining biological structure and function. These applications include processing electron micrographs to determine the three-dimensional structure of viruses, calculating the solvent accessible surface area of proteins to predict the three-dimensional conformation of these molecules from their primary structure, and searching for homologous DNA sequences in large genetic databases. Timing results demonstrate substantial performance improvements with parallel implementations compared with conventional sequential systems.

Original language	English (US)
Pages (from-to)	1386-1387
Number of pages	2
Journal	Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume	16
Issue number	pt 2
State	Published - 1994
Event	Proceedings of the 16th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Part 1 (of 2) - Baltimore, MD, USA Duration: Nov 3 1994 → Nov 6 1994

ASJC Scopus subject areas

Signal Processing
Biomedical Engineering
Computer Vision and Pattern Recognition
Health Informatics

Cite this

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title = "Role of high performance parallel computing in biological research",

abstract = "Scalable parallel computer architectures provide the computational performance demanded by advanced biological computing problems. NIH has developed a number of parallel algorithms and techniques useful in determining biological structure and function. These applications include processing electron micrographs to determine the three-dimensional structure of viruses, calculating the solvent accessible surface area of proteins to predict the three-dimensional conformation of these molecules from their primary structure, and searching for homologous DNA sequences in large genetic databases. Timing results demonstrate substantial performance improvements with parallel implementations compared with conventional sequential systems.",

author = "Martino, {Robert L.} and Johnson, {Calvin A.} and Suh, {Edward B.} and Trus, {Benes L.} and Yap, {Tieng K.}",

note = "Copyright: Copyright 2004 Elsevier B.V., All rights reserved.; Proceedings of the 16th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Part 1 (of 2) ; Conference date: 03-11-1994 Through 06-11-1994",

year = "1994",

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journal = "Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings",

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T1 - Role of high performance parallel computing in biological research

AU - Martino, Robert L.

AU - Johnson, Calvin A.

AU - Suh, Edward B.

AU - Trus, Benes L.

AU - Yap, Tieng K.

PY - 1994

Y1 - 1994

N2 - Scalable parallel computer architectures provide the computational performance demanded by advanced biological computing problems. NIH has developed a number of parallel algorithms and techniques useful in determining biological structure and function. These applications include processing electron micrographs to determine the three-dimensional structure of viruses, calculating the solvent accessible surface area of proteins to predict the three-dimensional conformation of these molecules from their primary structure, and searching for homologous DNA sequences in large genetic databases. Timing results demonstrate substantial performance improvements with parallel implementations compared with conventional sequential systems.

AB - Scalable parallel computer architectures provide the computational performance demanded by advanced biological computing problems. NIH has developed a number of parallel algorithms and techniques useful in determining biological structure and function. These applications include processing electron micrographs to determine the three-dimensional structure of viruses, calculating the solvent accessible surface area of proteins to predict the three-dimensional conformation of these molecules from their primary structure, and searching for homologous DNA sequences in large genetic databases. Timing results demonstrate substantial performance improvements with parallel implementations compared with conventional sequential systems.

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M3 - Conference article

AN - SCOPUS:0028758334

SN - 0589-1019

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EP - 1387

JO - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

JF - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

IS - pt 2

T2 - Proceedings of the 16th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Part 1 (of 2)

Y2 - 3 November 1994 through 6 November 1994

ER -

Role of high performance parallel computing in biological research

Abstract

ASJC Scopus subject areas

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