Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Biological or biochemical
Reexamination Certificate
2011-03-29
2011-03-29
Negin, Russell S (Department: 1631)
Data processing: measuring, calibrating, or testing
Measurement system in a specific environment
Biological or biochemical
C702S022000, C702S027000, C435S006120
Reexamination Certificate
active
07917302
ABSTRACT:
Sequence alignment and sequence database similarity searching are among the most important and challenging task in bio informatics, and are used for several purposes, including protein function prediction. An efficient parallelisation of the Smith-Waterman sequence alignment algorithm using parallel processing in the form of SIMD (Single-Instruction, Multiple-Data) technology is presented. The method has been implementation using the MMX (MultiMedia eXtensions) and SSE (Streaming SIMD Extensions) technology that is embedded in Intel's latest microprocessors, but the method can also be implemented using similar technology existing in other modern microprocessors. Near eight-fold speed-up relative to the fastest previously an optimised eight-way parallel processing approach achieved know non-parallel Smith-Waterman implementation on the same hardware. A speed of about 200 million cell updates per second has been obtained on a single Intel Pentium III 500 MHz microprocessor.
REFERENCES:
patent: 5485627 (1996-01-01), Hillis
patent: 5632041 (1997-05-01), Peterson et al.
patent: 6044419 (2000-03-01), Hayek et al.
patent: 0 360 527 (1990-03-01), None
Mount, David M. Bioinformatics: Sequence and Genome Analysis. Cold Spring Harbor Press, New York, 2000.
Smith and Waterman. Journal of Molecular Biology. 1981 vol. 147, pp. 195-197.
Rognes et al. Six-fold speed-up of Smith-Waterman sequence database searches using parallel processing on common microprocessors. Bioinformatics, vol. 18, 2000, pp. 699-706.
Brutlag et al. BLAZE: An implementation of the Smith Waterman seqeunce comparisom algorithm on a massively parallel computer. Computers & Chemistry, 1993, pp. 1-11 plus 6 graphics/captions pages.
Nicholas et al. Strategies for searching sequence databases. BioTechniques, vol. 28, Jun. 2000, pp. 1174-1176, 1178, 1180, 1182, 1184-1186, 1188-1189, 1191.
Hayes et al. Carbohydrate of the human plasminogen variants. The Journal of Biological Chemistry. vol. 254, 1979, pp. 8777-8780.
Rognes, Torbjorn et al.: Six-fold speed up of Smith-Waterman sequence database searches using parallel processing on common microprocessors. In: Bioinformatics, vol. 16, No. 8, Aug. 2000, pp. 699-706. See whole document.
Martins, W. S. et al.: A multithreaded parallel implementation of a dynamic programming algoritym for sequence comparison. Pacific Symposium on Biocomputing 2001, Jan. 3-7, 2001. See the whole document.
Lavenier, Dominique: Dedicated hardware for biological sequence comparison. In: Journal of Universal Computer Science 2 (2) 1996. See p. 4 and figure 3.
Erling Christen Seeberg
Harness Dickey & Pierce PLC
Negin Russell S
Torbjorn Rognes
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