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Data mining in proteomics

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Cover of 'Data mining in proteomics'

Table of Contents

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    Book Overview
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    Chapter 1 Instruments and Methods in Proteomics
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    Chapter 2 In-Depth Protein Characterization by Mass Spectrometry
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    Chapter 3 Analysis of Phosphoproteomics Data
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    Chapter 4 Data Mining in Proteomics
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    Chapter 5 Laboratory Data and Sample Management for Proteomics
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    Chapter 6 PRIDE and “Database on Demand” as Valuable Tools for Computational Proteomics
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    Chapter 7 Analysing Proteomics Identifications in the Context of Functional and Structural Protein Annotation: Integrating Annotation Using PICR, DAS, and BioMart
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    Chapter 8 Tranche Distributed Repository and ProteomeCommons.org
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    Chapter 9 Data Standardization by the HUPO-PSI: How has the Community Benefitted?
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    Chapter 10 mzIdentML: An Open Community-Built Standard Format for the Results of Proteomics Spectrum Identification Algorithms
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    Chapter 11 Spectra, Chromatograms, Metadata: mzML-The Standard Data Format for Mass Spectrometer Output
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    Chapter 12 imzML: Imaging Mass Spectrometry Markup Language: A Common Data Format for Mass Spectrometry Imaging
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    Chapter 13 Tandem Mass Spectrometry Spectral Libraries and Library Searching
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    Chapter 14 Inter-Lab Proteomics: Data Mining in Collaborative Projects on the Basis of the HUPO Brain Proteome Project’s Pilot Studies
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    Chapter 15 Data Management and Data Integration in the HUPO Plasma Proteome Project
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    Chapter 16 Statistics in Experimental Design, Preprocessing, and Analysis of Proteomics Data
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    Chapter 17 The Evolution of Protein Interaction Networks
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    Chapter 18 Cytoscape: software for visualization and analysis of biological networks.
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    Chapter 19 Data Mining in Proteomics
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    Chapter 20 Identification of alternatively spliced transcripts using a proteomic informatics approach.
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    Chapter 21 Distributions of ion series in ETD and CID spectra: making a comparison.
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    Chapter 22 Evaluation of Peak-Picking Algorithms for Protein Mass Spectrometry
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    Chapter 23 OpenMS and TOPP: Open Source Software for LC-MS Data Analysis
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    Chapter 24 LC/MS Data Processing for Label-Free Quantitative Analysis
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    Chapter 25 Spectral Properties of Correlation Matrices – Towards Enhanced Spectral Clustering
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    Chapter 26 Standards, Databases, and Modeling Tools in Systems Biology
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    Chapter 27 Modeling of Cellular Processes: Methods, Data, and Requirements
Attention for Chapter 24: LC/MS Data Processing for Label-Free Quantitative Analysis
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Chapter title
LC/MS Data Processing for Label-Free Quantitative Analysis
Chapter number 24
Book title
Data Mining in Proteomics
Published in
Methods in molecular biology, January 2011
DOI 10.1007/978-1-60761-987-1_24
Pubmed ID
Book ISBNs
978-1-60761-986-4, 978-1-60761-987-1
Authors

Patricia M. Palagi, Markus Müller, Daniel Walther, Frédérique Lisacek, Palagi, Patricia M., Müller, Markus, Walther, Daniel, Lisacek, Frédérique

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 1 6%
South Africa 1 6%
Austria 1 6%
Unknown 13 81%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 50%
Student > Ph. D. Student 4 25%
Professor 1 6%
Student > Doctoral Student 1 6%
Unknown 2 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 44%
Biochemistry, Genetics and Molecular Biology 5 31%
Physics and Astronomy 1 6%
Medicine and Dentistry 1 6%
Chemistry 1 6%
Other 0 0%
Unknown 1 6%