000			03409nam a2200349Ia 4500
001			CRC000E2801PDF
003			BD-DhSAU
005			20151012144301.0
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007			cr||||
008			121226s2013 fluad sb 001 0 eng d
020			_a9781420004304 (ebook : PDF)
040			_aBD-DhSAU _cBD-DhSAU
090			_aQH324.27 _b.D83 2013
092			_a572.330285 _bD812
100	1		_aDua, Sumeet.
245	1	0	_aData mining for bioinformatics _h[electronic resource] / _cSumeet Dua, Pradeep Chowriappa.
260			_aBoca Raton : _bCRC Press, _c2013.
300			_axix, 328 p. : _bill.
500			_a"An Auerbach book."
504			_aIncludes bibliographical references and index.
505	0		_a1. Introduction to bioinformatics -- 2. Biological databases and integration -- 3. Knowledge discovery in databases -- 4. Feature selection and extraction strategies in data mining -- 5. Feature interpretation for biological learning -- 6. Clustering techniques in bioinformatics -- 7. Advanced clustering techniques -- 8. Classification techniques in bioinformatics -- 9. Validation and benchmarking.
520			_a"PREFACE The flourishing field of bioinformatics has been the catalyst to transform biological research paradigms to extend beyond traditional scientific boundaries. Fueled by technological advancements in data collection, storage and analysis technologies in biological sciences, researchers have begun to increasingly rely on applications of computational knowledge discovery techniques to gain novel biological insight from the data. As we forge into the future of next-generation sequencing technologies, bioinformatics practitioners will continue to design, develop and employ new algorithms, that are efficient, accurate, scalable, reliable and robust to enable knowledge discovery on the projected exponential growth of raw data. To this end, data mining has been and will continue to be vital for analyzing large volumes of heterogeneous, distributed, semi-structured and interrelated data for knowledge discovery. This book is targeted to readers who are interested in the embodiments of data mining techniques, technologies and frameworks, employed for effective storing, analyzing, and extracting knowledge from large databases specifically encountered in a variety of bioinformatics domains, including but not limited to, genomics and proteomics. The book is also designed to give a broad, yet in-depth overview of the application domains of data mining for bioinformatics challenges. The sections of the book are designed to enable readers from both biology and computer science backgrounds gain an enhanced understanding of the cross-disciplinary field. In addition to providing an overview of the area discussed in Section 1, individual chapters of Sections 2, 3 and 4 are dedicated to key concepts of feature extraction, unsupervised learning, and supervised learning techniques"-- _cProvided by publisher.
530			_aAlso available in print edition.
538			_aMode of access: World Wide Web.
650		0	_aBioinformatics.
650		0	_aData mining.
655		7	_aElectronic books. _2lcsh
700	1		_aChowriappa, Pradeep, _eauthor.
776	1		_z9780849328015 (hardback)
856	4	0	_uhttp://marc.crcnetbase.com/isbn/9781420004304 _qapplication/PDF
999			_c11288 _d11287