Data Mining for Bioinformatics Applications
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In the end, I was not only able to survive summer classes, but I was able to thrive thanks to Course Hero. Sullivan University. CSC Uploaded By vsingi The extensive databases of biological information create both challenges and opportunities for development of novel KDD methods.
Data Mining for Bioinformatics Applications - ScholarVox International
Mining biological data helps to extract useful knowledge from massive datasets gathered in biology, and in other related life sciences areas such as medicine and neuroscience. 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.
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- Bioinformatics data mining: an introduction.
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.
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R China. His research interests include Computational proteomics and Biological data mining. Data Mining for Bioinformatics Applications. He Zengyou.