000			04352cam a2200529 i 4500
001			19096578
003			OSt
005			20241118065022.0
008			160516t20162016flua b 001 0 eng c
010			_a 2016304813
020			_a9781498724524 _q(Hardback)
020			_a1498724523 _q(Hardback)
035			_a(OCoLC)ocn913768150
040			_aYDXCP _beng _cYDXCP _erda _dBDX _dBTCTA _dOCLCQ _dCDX _dWAU _dKSU _dOCLCF _dDLC
042			_apcc
050	0	0	_aQH324.2 _b.B525 2016
084			_2Colon Classification
245	0	0	_aBig data analysis for bioinformatics and biomedical discoveries / _cedited by Shui Qing Ye.
264		1	_aBoca Raton : _bCRC Press, Taylor & Francis Group, _c[2016]
264		4	_c©2016
300			_axix, 273 pages : _billustrations ; _c24 cm.
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
490	1		_aChapman & Hall/CRC mathematical and computational biology series
500			_a"A Chapman & Hall book."
504			_aIncludes bibliographical references and index.
505	0		_aLinux for big data analysis / Shui Qing Ye and Ding-You Li -- Pythong for big data analysis / Dmitry N. Grigoryev -- R for big data analysis / Stephen D. Simon -- Genome-Seq data analysis / Min Xiong, Li Qin Zhang, and Shui Qing Ye -- RNA-seq data analysis / Li Qin Zhang, Min Xiong, Daniel P. Heruth, and Shui Qing Ye -- Microbiome-seq data analysis / Daniel P. Heruth, Min Xiong, and Xun Jiang -- miRNA-seq data analysis / Daniel P. Heruth, Min Xiong, and Guang-Liand Bi -- Methylome-seq data analysis / Chengpeng Bi -- ChIP-seq data analysis / Shui Qing Ye, Li Qin Zhang, and Jiancheng Tu -- Integrating omics data in big data analysis / Li Qin Zhang, Daniel P. Heruth, and Shui Qing Ye -- Pharmacogenetics and genomics / Andrea Gaedigk, Katrin Sangkuhl, and Larisa H. Cavallari -- Exploring de-identified electronic health record data with i2b2 / Mark Hoffman -- Big data and drug discovery / Gerald J. Wyckoff and D. Andrew Skaff -- Literature-based knowledge discovery / Hongfanf Liu and Majid Rastegar-Mojarad -- Mitigating high dimensionality in big data / Deendayal Dinakarpandian.
520			_a"Big Data Analysis for Bioinformatics and Biomedical Discoveries provides a practical guide to the nuts and bolts of Big Data, enabling you to quickly and effectively harness the power of Big Data to make groundbreaking biological discoveries, carry out translational medical research, and implement personalized genomic medicine. Contributing to the NIH Big Data to Knowledge (BD2K) initiative, the book enhances your computational and quantitative skills so that you can exploit the Big Data being generated in the current omics era. The book explores many significant topics of Big Data analyses in an easily understandable format. It describes popular tools and software for Big Data analyses and explains next-generation DNA sequencing data analyses. It also discusses comprehensive Big Data analyses of several major areas, including the integration of omics data, pharmacogenomics, electronic health record data, and drug discovery. Accessible to biologists, biomedical scientists, bioinformaticians, and computer data analysts, the book keeps complex mathematical deductions and jargon to a minimum. Each chapter includes a theoretical introduction, example applications, data analysis principles, step-by-step tutorials, and authoritative references"-- _cBack cover.
650		0	_aBioinformatics.
650		0	_aMedical sciences _xData processing.
650		0	_aSequence alignment (Bioinformatics)
650		0	_aNucleotide sequence.
650		0	_aData mining.
650		0	_aBig data.
650		7	_aBig data. _2fast _0(OCoLC)fst01892965
650		7	_aBioinformatics. _2fast _0(OCoLC)fst00832181
650		7	_aData mining. _2fast _0(OCoLC)fst00887946
650		7	_aMedical sciences _xData processing. _2fast _0(OCoLC)fst01014605
650		7	_aNucleotide sequence. _2fast _0(OCoLC)fst01041106
650		7	_aSequence alignment (Bioinformatics) _2fast _0(OCoLC)fst01747147
700	1		_aYe, Shui Qing, _d1954- _eeditor.
830		0	_aChapman & Hall/CRC mathematical and computational biology series.
906			_a7 _bcbc _cpccadap _d2 _encip _f20 _gy-gencatlg
942			_2ddc _cBK
999			_c741356 _d741356