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Biological Data Mining Chapman Hall Crc Data Mining And Knowledge Discovery Series 1st Edition Jake Y Chen

  • SKU: BELL-2172726
Biological Data Mining Chapman Hall Crc Data Mining And Knowledge Discovery Series 1st Edition Jake Y Chen
$ 31.00 $ 45.00 (-31%)

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Biological Data Mining Chapman Hall Crc Data Mining And Knowledge Discovery Series 1st Edition Jake Y Chen instant download after payment.

Publisher: Chapman and Hall/CRC
File Extension: PDF
File size: 5.43 MB
Pages: 736
Author: Jake Y. Chen, Stefano Lonardi
ISBN: 1420086847
Language: English
Year: 2009
Edition: 1

Product desciption

Biological Data Mining Chapman Hall Crc Data Mining And Knowledge Discovery Series 1st Edition Jake Y Chen by Jake Y. Chen, Stefano Lonardi 1420086847 instant download after payment.

Like a data-guzzling turbo engine, advanced data mining has been powering post-genome biological studies for two decades. Reflecting this growth, Biological Data Mining presents comprehensive data mining concepts, theories, and applications in current biological and medical research. Each chapter is written by a distinguished team of interdisciplinary data mining researchers who cover state-of-the-art biological topics. The first section of the book discusses challenges and opportunities in analyzing and mining biological sequences and structures to gain insight into molecular functions. The second section addresses emerging computational challenges in interpreting high-throughput Omics data. The book then describes the relationships between data mining and related areas of computing, including knowledge representation, information retrieval, and data integration for structured and unstructured biological data. The last part explores emerging data mining opportunities for biomedical applications. This volume examines the concepts, problems, progress, and trends in developing and applying new data mining techniques to the rapidly growing field of genome biology. By studying the concepts and case studies presented, readers will gain significant insight and develop practical solutions for similar biological data mining projects in the future.

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