000			03387nam a22004455i 4500
001			u371185
003			SIRSI
005			20160812080114.0
007			cr nn 008mamaa
008			100301s2010 xxu| s |||| 0|eng d
020			_a9781441908117 _9978-1-4419-0811-7
040			_cMX-MeUAM
050		4	_aRC261-271
082	0	4	_a614.5999 _223
100	1		_aPham, Tuan. _eeditor.
245	1	0	_aComputational Biology _h[recurso electrónico] : _bIssues and Applications in Oncology / _cedited by Tuan Pham.
264		1	_aNew York, NY : _bSpringer New York, _c2010.
300			_aVIII, 309p. 90 illus., 26 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aApplied Bioinformatics and Biostatistics in Cancer Research
505	0		_aIdentification of Relevant Genes from Microarray Experiments based on Partial Least Squares Weights: Application to Cancer Genomics -- Geometric Biclustering and Its Applications to Cancer Tissue Classification Based on DNA Microarray Gene Expression Data -- Statistical Analysis on Microarray Data: Selection of Gene Prognosis Signatures -- Agent-Based Modeling of Ductal Carcinoma In Situ: Application to Patient-Specific Breast Cancer Modeling -- Multicluster Class-Based Classification for the Diagnosis of Suspicious Areas in Digital Mammograms -- Analysis of Cancer Data Using Evolutionary Computation -- Analysis of Population-Based Genetic Association Studies Applied to Cancer Susceptibility and Prognosis -- Selected Applications of Graph-Based Tracking Methods for Cancer Research -- Recent Advances in Cell Classification for Cancer Research and Drug Discovery -- Computational Tools and Resources for Systems Biology Approaches in Cancer -- Laser Speckle Imaging for Blood Flow Analysis -- The Challenges in Blood Proteomic Biomarker Discovery.
520			_aComputational Biology: Issues and Applications in Oncology provides a comprehensive report on recent techniques and results in computational oncology essential to the knowledge of scientists, engineers, as well as postgraduate students working on the areas of computational biology, bioinformatics, and medical informatics. With chapters timely prepared and written by experts in the field, this in-depth and up-to-date volume covers advanced statistical methods, heuristic algorithms, cluster analysis, data modeling, image and pattern analysis applied to cancer research. The literature and coverage of a spectrum of key topics in issues and applications in oncology make this a useful resource to computational life-science researchers wishing to enhance the most recent knowledge to facilitate their own investigations.
650		0	_aMedicine.
650		0	_aOncology.
650		0	_aToxicology.
650	1	4	_aBiomedicine.
650	2	4	_aCancer Research.
650	2	4	_aPharmacology/Toxicology.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9781441908100
830		0	_aApplied Bioinformatics and Biostatistics in Cancer Research
856	4	0	_zLibro electrónico _uhttp://148.231.10.114:2048/login?url=http://link.springer.com/book/10.1007/978-1-4419-0811-7
596			_a19
942			_cLIBRO_ELEC
999			_c199065 _d199065