000			03362nam a2200397 i 4500
005			20250930145407.0
008			150428t20132013flua bi 001 0 eng
020			_a9780849328015 _q(hardback) _cRM345.94
039		9	_a201601071204 _bbaiti _c201512180900 _dhaiyati _c201511261520 _drahah _y04-28-2015 _zrahah
040			_aDLC _beng _cDLC _erda _dDLC _dUKM _erda
090			_aQH324.27.D83S864 3
090	0	0	_aQH324.27 _b.D83S864 3
100	1		_aDua, Sumeet, _eauthor.
245	1	0	_aData mining for bioinformatics / _cSumeet Dua, Pradeep Chowriappa.
264		1	_aBoca Raton : _bCRC Press/Taylor & Francis Group, _c2013.
264		4	_c©2013
300			_axix, 328 pages : _billustrations ; _c24 cm.
336			_atext _2rdacontent
337			_aunmediated _2rdamedia
338			_avolume _2rdacarrier
500			_a'An Auerback book.'
504			_aIncludes bibliographical references and index.
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.
650		0	_aBioinformatics. _962472
650		0	_aData mining.
700	1		_aChowriappa, Pradeep, _eauthor.
856	4	2	_3Cover image _uhttp://jacketsearch.tandf.co.uk/common/jackets/covers/websmall/978084932/9780849328015.jpg
907			_a.b1613249x _b2019-11-12 _c2019-11-12
942			_c01 _n0 _kQH324.27.D83S864 3
914			_avtls003585117
990			_anh
991			_aFakulti Teknologi dan Sains Maklumat
998			_al _b2015-02-04 _cm _da _feng _gflu _y0 _z.b1613249x
999			_c684236 _d684236