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CEC
2008
IEEE

Evolving GeneChip correlation predictors on parallel graphics hardware

14 years 20 days ago
Evolving GeneChip correlation predictors on parallel graphics hardware
—A GPU is used to datamine five million correlations between probes within Affymetrix HG-U133A probesets across 6685 human tissue samples from NCBI’s GEO database. These concordances are used as machine learning training data for genetic programming running on a Linux PC with a RapidMind OpenGL GLSL backend. GPGPU is used to identify technological factors influencing High Density Oligonuclotide Arrays (HDONA) performance. GP suggests mismatch (PM/MM) and Adenosine/Guanine ratio influence microarray quality. Initial results hint that Watson-Crick probe self hybridisation or folding is not important. Under GPGPGPU an nVidia GeForce 8800 GTX interprets 300 million GP primitives/second (300 MGPops, approx 8 GFLOPS).
William B. Langdon
Added 29 May 2010
Updated 29 May 2010
Type Conference
Year 2008
Where CEC
Authors William B. Langdon
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