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International Conference on Computing: Theory and Applications (ICCTA'07)
Kolkata, India
March 05-March 07
ISBN: 0-7695-2770-1
Xuegong Zhang, Tsinghua University, China
The current molecular biology and systems biology is featured by the rapid accumulation of high-throughput genomics and proteomics data like microarray and mass spectrometry (MS) data. Typical applications of these high-throughput biological data include the use of microarray or MS data for the molecular classification of complex human diseases like cancers, and for discovering the genes/protein markers (biomarkers) underlying the classification. Such tasks have been intensively studied as a new application field of pattern recognition in recent years. Almost all existing methods for classification and feature selection have been tried, and a large number of new or revised methods have been proposed.
Citation:
Xuegong Zhang, "Pattern Recognition in Mining High-Throughput Genomics/Proteomics Data: The New Challenges in Old Questions," iccta, pp.242-244, International Conference on Computing: Theory and Applications (ICCTA'07), 2007
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