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008			161214s2017 xxu| s |||| 0|eng d
020			_a9781493967407
024	7		_a10.1007/978-1-4939-6740-7 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC
245	1	0	_aProteome Bioinformatics _cedited by Shivakumar Keerthikumar, Suresh Mathivanan.
250			_a1st edition 2017
264		1	_aNew York, NY _bSpringer International Publishing _c2017
300			_a1 recurso en línea (XI, 233 páginas) _b51 ilustraciones, 40 ilustraciones a color
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 _v1549
505	0		_aAn Introduction to Proteome Bioinformatics -- Proteomic Data Storage and Sharing -- Choosing an Optimal Database for Protein Identification from Tandem Mass Spectrometry Data -- Label-Based and Label-Free Strategies for Protein Quantitation -- TMT One Stop Shop: From Reliable Sample Preparation to Computational Analysis Platform -- Unassigned MS/MS Spectra: Who Am I? -- Methods to Calculate Spectrum Similarity -- Proteotypic Peptides and Their Applications -- Statistical Evaluation of Labeled Comparative Profiling Proteomics Experiments Using Permutation Test -- De Novo Peptide Sequencing: Deep Mining of High-Resolution Mass Spectrometry Data -- Phylogenetic Analysis Using Protein Mass Spectrometry -- Bioinformatics Methods to Deduce Biological Interpretation from Proteomics Data -- A Systematic Bioinformatics Approach to Identify High Quality Mass Spectrometry Data and Functionally Annotate Proteins and Proteomes -- Network Tools for the Analysis of Proteomic Data -- Determining the Significance of Protein Network Features and Attributes Using Permutation Testing -- Bioinformatics Tools and Resources for Analyzing Protein Structures -- In Silico Approach to Identify Potential Inhibitors for Axl-Gas6 Signalling.
520			_aThis thorough book covers the most recent proteomics techniques, databases, bioinformatics tools, and computational approaches that are used for the identification and functional annotation of proteins and their structure. The most recent proteomic resources widely used in the biomedical scientific community for storage and dissemination of data are discussed. In addition, specific MS/MS spectrum similarity scoring functions and their application in the field of proteomics, statistical evaluation of labeled comparative proteomics using permutation testing, and methods of phylogenetic analysis using MS data are also described in detail. Written for the highly successful Methods in Molecular Biology series, chapters contain the kind of detail and key implementation advice to ensure successful results. Authoritative and cutting-edge, Proteome Bioinformatics serves as a useful resource for researchers who are beginners as well as advanced investigators in the field of proteomics.
700	1		_aKeerthikumar, Shivakumar _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aMathivanan, Suresh _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
776	0	8	_iPrinted edition: _z9781493967384
776	0	8	_iPrinted edition: _z9781493967391
776	0	8	_iPrinted edition: _z9781493982882
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-1-4939-6740-7 _z(usuarios Universidad Europea de Valencia)
942			_2lcc _cLE
988			_aSpringer_Protocols_2017
999			_c235089 _d235089