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Data mining in proteomics : from standards to applications

Author: Michael Hamacher; Martin Eisenacher; Christian Stephan
Publisher: New York, N.Y. : Humana Press, ©2011.
Series: Methods in molecular biology (Clifton, N.J.), v. 696.; Springer protocols (Series)
Edition/Format:   Print book : EnglishView all editions and formats
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Data Mining in Proteomics presents new insights within the proteomics community, while taking into account the historical evolution and international standardization projects. The text presents  Read more...

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Material Type: Internet resource
Document Type: Book, Internet Resource
All Authors / Contributors: Michael Hamacher; Martin Eisenacher; Christian Stephan
ISBN: 9781607619864 1607619865
OCLC Number: 648933072
Description: xii, 461 pages : illustrations (some color) ; 27 cm.
Contents: Instruments and methods in proteomics / Caroline May [and others] --
In depth protein characterization by mass spectrometry / Daniel Chamrad, Gerhard Körting, and Martin Blüggel --
Analysis of phosphoproteomics data / Christoph Schaab --
The origin and early reception of sequence databases / Joel B. Hagen --
Laboratory data and sample management for proteomics / Jari Häkkinen and Fredrik Levander --
PRIDE and "database on demand" as valuable tools for computational proteomics / Juan Antonio Vizcaíno [and others] --
Analysing proteomics identifications in the context of functional and structural protein annotation : integrating annotation using PICR, DAS, and BioMart / Philip Jones --
Tranche distributed repository and ProteomeCommons.org / Bryan E. Smith [and others] --
Data standardization by the HUPO-PSI : how has the community benefitted? / Sandra Orchard and Henning Hermjakob --
mzIdentML : an open community-built standard format for the results of proteomics spectrum identification algorithms / Martin Eisenacher --
Spectra, chromatograms, metadata : mzML-the standard data format for mass spectrometer output / Michael Turewicz and Eric W. Deutsch --
imzML : imaging mass spectrometry markup language : a common data format for mass spectrometry imaging / Andreas Römpp [and others] --
Tandem mass spectrometry spectral libraries and library searching / Eric W. Deutsch --
Inter-lab proteomics : data mining in collaborative projects on the basis of the HUPO Brain Proteome Project's pilot studies / Michael Hamacher [and others] --
Data management and data integration in the HUPO Plasma Proteome Project / Gilbert S. Omenn --
Statistics in experimental design, preprocessing, and analysis of proteomics data / Klaus Jung --
The evolution of protein interaction networks / Andreas Schüler and Erich Bornberg-Bauer --
Cytoscape : software for visualization and analysis of biological networks / Michael Kohl, Sebastian Wiese, and Bettina Warscheid --
Text mining for systems modeling / Axel Kowald and Seastian Schmeier --
Identification of alternatively spliced transcripts using a proteomic informatics approach / Rajasree Menon and Gilbert S. Omenn --
Distributions of ion series in ETD and CID spectra : making a comparison / Sarah R. Hart [and others] --
Evaluation of peak-picking algorighms for protein mass spectrometry / Chris Bauer, Rainer Cramer, and Johannes Schuchhardt --
OpenMS and TOPP : open source software for LC-MS data analysis / Andreas Bertsch [and others] --
LC/MS data processing for label-free quantitative analysis / Patricia M. Palagi [and others] --
Spectral properties of correlation matrices-towards enhanced spectral clustering / Daniel Fulger and Enrico Scalas --
Standards, databases, and modeling tools in systems biology / Michael Kohl --
Modeling of cellular processes : methods, data, and requirements / Thomas Millat [and others].
Series Title: Methods in molecular biology (Clifton, N.J.), v. 696.; Springer protocols (Series)
Responsibility: edited by Michael Hamacher, Martin Eisenacher, and Christian Stephan.

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From the reviews:"The field of data mining in proteomics is currently extremely dynamic while encompassing a wide range of specialties, topics and implications, and so is this book. ... This is a Read more...

 
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