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020 _a9781603271943
_9978-1-60327-194-3
024 7 _a10.1007/978-1-60327-194-3
_2doi
050 4 _aQH324.2-324.25
072 7 _aUY
_2bicssc
072 7 _aPS
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072 7 _aCOM082000
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072 7 _aPSAX
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082 0 4 _a570.285
_223
245 1 0 _aBioinformatics Methods in Clinical Research
_h[electronic resource] /
_cedited by Rune Matthiesen.
250 _a1st ed. 2010.
264 1 _aTotowa, NJ :
_bHumana Press :
_bImprint: Humana,
_c2010.
300 _aX, 390 p. 63 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _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.
650 0 _aBioinformatics.
650 1 4 _aBioinformatics.
650 2 4 _aComputational and Systems Biology.
700 1 _aMatthiesen, Rune.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9781603271936
776 0 8 _iPrinted edition:
_z9781607613824
776 0 8 _iPrinted edition:
_z9781617796708
830 0 _aMethods in Molecular Biology,
_x1940-6029 ;
_v593
856 4 0 _uhttps://doi.org/10.1007/978-1-60327-194-3
912 _aZDB-2-PRO
999 _c6743
_d6743