000			03480nam a22003615i 4500
001			234006
003			ES-VaUE
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007			cr nn 008mamaa
008			100715s2010 xxu| s |||| 0|eng d
020			_a9781603271943
024	7		_a10.1007/978-1-60327-194-3 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC
245	1	0	_aBioinformatics Methods in Clinical Research _cedited by Rune Matthiesen.
250			_a1st edition 2010
264		1	_aTotowa, NJ _bHumana Press _c2010
300			_a1 recurso en línea (X, 390 páginas) _b63 ilustraciones
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aMethods in Molecular Biology _x1940-6029 _v593
505	0		_ato Omics -- Machine Learning: An Indispensable Tool in Bioinformatics -- SNP-PHAGE: High-Throughput SNP Discovery Pipeline -- R Classes and Methods for SNP Array Data -- Overview on Techniques in Cluster Analysis -- Nonalcoholic Steatohepatitis, Animal Models, and Biomarkers: What Is New? -- Biomarkers in Breast Cancer -- Genome-Wide Proximal Promoter Analysis and Interpretation -- Proteomics Facing the Combinatorial Problem -- Methods and Algorithms for Relative Quantitative Proteomics by Mass Spectrometry -- Feature Selection and Machine Learning with Mass Spectrometry Data -- Computational Methods for Analysis of Two-Dimensional Gels -- Mass Spectrometry in Epigenetic Research -- Computational Approaches to Metabolomics -- Algorithms and Methods for Correlating Experimental Results with Annotation Databases -- Analysis of Biological Processes and Diseases Using Text Mining Approaches.
520			_aIntegrated bioinformatics solutions have become increasingly valuable in past years, as technological advances have allowed researchers to consider the potential of omics for clinical diagnosis, prognosis, and therapeutic purposes, and as the costs of such techniques have begun to lessen. In Bioinformatics Methods in Clinical Research, experts examine the latest developments impacting clinical omics, and describe in great detail the algorithms that are currently used in publicly available software tools. Chapters discuss statistics, algorithms, automated methods of data retrieval, and experimental consideration in genomics, transcriptomics, proteomics, and metabolomics. Composed in the highly successful Methods in Molecular Biology™ series format, each chapter contains a brief introduction, provides practical examples illustrating methods, results, and conclusions from data mining strategies wherever possible, and includes a Notes section which shares tips on troubleshooting and avoiding known pitfalls. Informative and ground-breaking, Bioinformatics Methods in Clinical Research establishes a much-needed bridge between theory and practice, making it an indispensable resource for bioinformatics researchers.
700	1		_aMatthiesen, Rune _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
776	0	8	_iPrinted edition: _z9781607613824
776	0	8	_iPrinted edition: _z9781617796708
776	0	8	_iPrinted edition: _z9781603271936
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-1-60327-194-3 _z(usuarios Universidad Europea de Valencia)
942			_2lcc _cLE
988			_aSpringer_Protocols_2010
999			_c234006 _d234006