000			02069nam a22003378i 4500
001			CR9781107706484
003			UkCbUP
005			20200124160217.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			131105s2015||||enk o ||1 0|eng|d
020			_a9781107706484 (ebook)
020			_z9781107069114 (hardback)
020			_z9781107697577 (paperback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aQH438.4.S73 _bT74 2015
082	0	0	_a572.8/6 _223
100	1		_aTseng, George, _eauthor.
245	1	0	_aIntegrating omics data / _cGeorge Tseng, University of Pittsburgh, Debashis Ghosh, the Pennsylvania State University, Xianghong Jasmine, University of Southern California.
264		1	_aCambridge : _bCambridge University Press, _c2015.
300			_a1 online resource (x, 461 pages) : _bdigital, PDF file(s).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
500			_aTitle from publisher's bibliographic system (viewed on 05 Oct 2015).
520			_aIn most modern biomedical research projects, application of high-throughput genomic, proteomic, and transcriptomic experiments has gradually become an inevitable component. Popular technologies include microarray, next generation sequencing, mass spectrometry and proteomics assays. As the technologies have become mature and the price affordable, omics data are rapidly generated, and the problem of information integration and modeling of multi-lab and/or multi-omics data is becoming a growing one in the bioinformatics field. This book provides comprehensive coverage of these topics and will have a long-lasting impact on this evolving subject. Each chapter, written by a leader in the field, introduces state-of-the-art methods to handle information integration, experimental data, and database problems of omics data.
650		0	_aGenomics _xStatistical methods.
650		0	_aMeta-analysis.
776	0	8	_iPrint version: _z9781107069114
856	4	0	_uhttps://doi.org/10.1017/CBO9781107706484
999			_c516355 _d516353