Predictive modeling in proteomics-based disease detection
Pham, Tuan (2007) Predictive modeling in proteomics-based disease detection. In: Proceedings of the 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 3308-3311. From: 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 23-26 August 2007, Lyon, France.
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Recent advent of mass-spectrometry data generated by proteomic technology provides a new type of biological information which is very promising in the search for diagnostic and therapeutic approaches that enables the early detection of fatal diseases and the development of personalized medicine. Successful analysis of such high-throughput proteomic data relies much on signal-processing and pattern-recognition techniques. This paper addresses the application of prediction models for cancer detection using mass spectral data.
|Item Type:||Conference Item (Refereed Research Paper - E1)|
|Keywords:||pattern recognition; bioinformatics|
|Date Deposited:||01 Oct 2009 02:02|
|FoR Codes:||08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining @ 50%
08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080106 Image Processing @ 50%
|SEO Codes:||89 INFORMATION AND COMMUNICATION SERVICES > 8902 Computer Software and Services > 890205 Information Processing Services (incl. Data Entry and Capture) @ 100%|
|Citation Count from Web of Science||