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Data Mining for Bioinformatics Applications provides valuable information on the data mining methods have been widely used for solving real bioinformatics problems, including problem definition, data collection, data preprocessing, modeling, and validation.

The text uses an example-based method to illustrate how to apply data mining techniques to solve real bioinformatics problems, containing 45 bioinformatics problems that have been investigated in recent research. For each example, the entire data mining process is described, ranging from data preprocessing to modeling and result validation.

Provides valuable information on the data mining methods have been widely used for solving real bioinformatics problems
Uses an example-based method to illustrate how to apply data mining techniques to solve real bioinformatics problems
Contains 45 bioinformatics problems that have been investigated in recent research

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Chapter 1: An overview of data mining Chapter 2: Introduction to bioinformatics Chapter 3: Phosphorylation motif discovery Chapter 4: Phosphorylation site prediction Chapter 5: Protein inference in shotgun proteomics Chapter 6: Protein-protein interaction network construction from AP-MS data Chapter 7: Protein complex identification from AP-MS data Chapter 8: Biomarker discovery

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Zengyou, He
Zengyou He is an Associate Professor at the School of Software, Dalian University of Technology, P.R China. He received his BS, MS, and PhD in Computer science from Harbin Institute of Technology, P.R China and was a Research associate in the Department of Electronic and Computer Engineering at the Hong Kong University of Science and Technology from 2007 to 2010. His research interests include Computational proteomics and Biological data mining. He has published more than 20 papers on leading journals in the field of bioinformatics, including Bioinformatics, BMC Bioinformatics, Briefings in Bioinformatics, IEEE/ACM Transactions on Computational Biology and Bioinformatics and Journal of Computational Biology.

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