000			04392cam a2200757Ii 4500
001			ocn834600291
003			OCoLC
005			20230823095530.0
006			m o d
007			cr |||||||||||
008			130225t20132013gw ad ob 001 0 eng d
040			_aE7B _beng _erda _epn _cE7B _dOCLCQ _dOCLCO _dDG1 _dCUS _dYDXCP _dNOC _dOCLCQ _dOCLCO _dOCLCF _dGGVRL _dEBLCP _dCDX _dMMU _dCOO
019			_a827207495 _a828617831 _a881385141
020			_a9783527665471 _q(oBook)
020			_a3527665471 _q(oBook)
020			_a9783527665440 _q(ePDF)
020			_a3527665447 _q(ePDF)
020			_a9783527665457 _q(ePUB)
020			_a3527665455 _q(ePUB)
020			_a9781299158511 _q(MyiLibrary)
020			_a129915851X _q(MyiLibrary)
020			_a9783527665464 _q(Mobi)
020			_a3527665463 _q(Mobi)
020			_z9783527332625 _q(print : alk. paper)
020			_z3527332626 _q(print : alk. paper)
029	1		_aAU@ _b000051628924
029	1		_aNZ1 _b15340129
029	1		_aDEBBG _bBV041069279
029	1		_aCHVBK _b306231468
029	1		_aCHBIS _b010026922
029	1		_aDEBBG _bBV043395700
035			_a(OCoLC)834600291 _z(OCoLC)827207495 _z(OCoLC)828617831 _z(OCoLC)881385141
037			_a447101 _bMIL
050		4	_aRC270 _b.S73 2013eb
060		4	_aQZ 241
072		7	_aHEA _2eflch
082	0	4	_a616.99/4075 _223
049			_aMAIN
245	0	0	_aStatistical diagnostics for cancer : _banalyzing high-dimensional data / _cedited by Frank Emmert-Streib and Matthias Dehmer.
250			_aFirst edition.
264		1	_aWeinheim, Germany : _bWiley-Blackwell, _c[2013]
264		4	_c©2013
300			_a1 online resource (xx, 292 pages) : _billustrations (some color).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
490	1		_aQuantitative and network biology ; _vvolume 3
500			_aEdition statement from running title area.
504			_aIncludes bibliographical references and index.
505	0		_aPart one: General overview. Control of type I error rates for oncology biomarker discovery with high-throughput platforms -- Overview of public cancer databases, resources, and visualization tools -- Part two: Bayesian methods. Discovery of expression signatures in chronic myeloid leukemia by Bayesian model averaging -- Bayesian ranking and selection methods in microarray studies -- Multiclass classification via Bayesian variable selection with gene expression data -- Semisupervised methods for analyzing high-dimensional genomic data -- Part three: Network-based approaches -- Colorectal cancer and its molecular subsystems: construction, interpretation, and validation -- Network medicine: disease genes in molecular networks -- Inference of gene regulatory networks in breast and ovarian cancer by integrating different genomic data -- Network-module-based approaches in cancer data analysis -- Discriminant and network analysis to study origin of cancer -- Intervention and control of gene regulatory networks: theoretical framework and application to human melanoma gene regulation -- Part four: Phenotype influence of DNA copy number aberrations. Identification of recurrent DNA copy number aberrations in tumors -- The cancer cell, its entropy, and high-dimensional molecular data.
520			_aThis title discusses different methods for statistically analyzing and validating data created with high-throughput methods. It focuses on systems approaches, meaning that no single gene or protein forms the basis of the analysis but rather a more or less complex biological network.
588			_aDescription based on online resource; title from resource home page (ebrary, viewed October 8, 2015).
650		0	_aCancer _xDiagnosis.
650		2	_aNeoplasms _xgenetics.
650		2	_aStatistics as Topic _xmethods.
650		7	_aCancer _xDiagnosis. _2fast _0(OCoLC)fst00845345
655		4	_aElectronic books.
655		7	_aElectronic books. _2local
700	1		_aEmmert-Streib, Frank, _eeditor.
700	1		_aDehmer, Matthias, _d1968- _eeditor.
776	0	8	_iPrint version: _tStatistical diagnostics for cancer. _dWeinheim, germany : Wiley-Blackwell, [2013] _z9783527332625 _w(OCoLC)840878109
830		0	_aQuantitative and network biology ; _vv. 3.
856	4	0	_uhttp://dx.doi.org/10.1002/9783527665471 _zWiley Online Library
994			_a92 _bDG1
999			_c20365 _d20324
526			_bls