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Our ability to generate and collect data has been increasing rapidly. Improving data delivery is the top priority in bio computing today this comprehensive cutting edge guide can help by showing you how to effectively integrate bioinformatics and other powerful data mining technologies. This compact book explores the concept of data mining and discusses various data mining techniques and their applications towards bioinformatics. It is primarily designed for budding researchers in computer science. You will learn how to Use data mining to establish competitive advantage, Solve biological…mehr

Produktbeschreibung
Our ability to generate and collect data has been increasing rapidly. Improving data delivery is the top priority in bio computing today this comprehensive cutting edge guide can help by showing you how to effectively integrate bioinformatics and other powerful data mining technologies. This compact book explores the concept of data mining and discusses various data mining techniques and their applications towards bioinformatics. It is primarily designed for budding researchers in computer science. You will learn how to Use data mining to establish competitive advantage, Solve biological problems faster by exploiting clustering and pattern discovery ,Evaluate various data mining solutions to the high dimensional datasets, Leverage your data mining utility via the internet, other biological resources i.e, medical datasets, bioinformatics datasets etc, In addition to provide a detailed overview and strategic analysis of the available data mining technologies, the book serves as a practical guide to design and deployment of algorithms and how to interpret, evaluate and discuss according to our research for the research scholars.
Autorenporträt
Dr. M. Hemalatha (Ph.D,Mother Terasa women s Univeristy, Kodaikanal) is Professor& Head and guiding Ph.D scholars in the Department of Computer Science in Karpagam University, Coimbatore. She has published over 157 papers in Intl. journals and conf. Her research is on Data mining, image processing, computational biology and soft computing domains.