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Bioinformatics of Human Proteomics

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Cover of 'Bioinformatics of Human Proteomics'

Table of Contents

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    Book Overview
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    Chapter 1 Clinical Bioinformatics in Human Proteomics Research
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    Chapter 2 Proteomics Defines Protein Interaction Network of Signaling Pathways
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    Chapter 3 Protein Function Microarrays: Design, Use and Bioinformatic Analysis in Cancer Biomarker Discovery and Quantitation
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    Chapter 4 Proteomics and Cancer Research
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    Chapter 5 Toward Development of Novel Peptide-Based Cancer Therapeutics: Computational Design and Experimental Evaluation
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    Chapter 6 Advances in Proteomic Methods
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    Chapter 7 Clinical and Biomedical Mass Spectrometry: New Frontiers in Drug Developments and Diagnosis
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    Chapter 8 Disease Biomarkers: Modelling MR Spectroscopy and Clinical Applications
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    Chapter 9 Processing of Mass Spectrometry Data in Clinical Applications
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    Chapter 10 Bioinformatics Approach for Finding Target Protein in Infectious Disease
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    Chapter 11 Identification of Network Biomarkers for Cancer Diagnosis
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    Chapter 12 Software Development for Quantitative Proteomics Using Stable Isotope Labeling
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    Chapter 13 Clinical Translation of Protein Biomarkers Integrated with Bioinformatics
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    Chapter 14 Proteomic Approaches for Urine Biomarker Discovery in Bladder Cancer
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    Chapter 15 Antibody Microarrays and Multiplexing
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    Chapter 16 Proteomics in Anaesthesia and Intensive Care Medicine
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    Chapter 17 Erratum
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Title
Bioinformatics of Human Proteomics
Published by
Springer Netherlands, January 2013
DOI 10.1007/978-94-007-5811-7
ISBNs
978-9-40-075810-0, 978-9-40-075811-7
Editors

Wang, Xiangdong

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Mexico 1 2%
Brazil 1 2%
Unknown 50 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 17%
Other 6 12%
Researcher 6 12%
Student > Master 4 8%
Student > Bachelor 4 8%
Other 4 8%
Unknown 19 37%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 21%
Biochemistry, Genetics and Molecular Biology 6 12%
Medicine and Dentistry 3 6%
Mathematics 2 4%
Chemistry 2 4%
Other 5 10%
Unknown 23 44%