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Proteome Bioinformatics

  • Book
  • © 2017

Overview

Editors:
  1. Shivakumar Keerthikumar

    1. Department of Biochemistry and Genetics, La Trobe Institute for Molecular Science, La Trobe University, Melbourne, Australia

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    You can also search for this editor in PubMed   Google Scholar

  2. Suresh Mathivanan

    1. Department of Biochemistry and Genetics, La Trobe Institute for Molecular Science, La Trobe University, Melbourne, Australia

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  • Includes cutting-edge techniques for studying bioinformatics of the proteome
  • Provides step-by-step detail essential for reproducible results
  • Contains key implementation advice from the experts
  • Includes supplementary material: sn.pub/extras

Part of the book series: Methods in Molecular Biology (MIMB, volume 1549)

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Table of contents (17 protocols)

  1. Front Matter

    Pages i-xi
    Download chapter PDF

  2. An Introduction to Proteome Bioinformatics

    • Shivakumar Keerthikumar
    Pages 1-3

  3. Proteomic Data Storage and Sharing

    • Shivakumar Keerthikumar, Suresh Mathivanan
    Pages 5-15

  4. Choosing an Optimal Database for Protein Identification from Tandem Mass Spectrometry Data

    • Dhirendra Kumar, Amit Kumar Yadav, Debasis Dash
    Pages 17-29

  5. Label-Based and Label-Free Strategies for Protein Quantitation

    • Sushma Anand, Monisha Samuel, Ching-Seng Ang, Shivakumar Keerthikumar, Suresh Mathivanan
    Pages 31-43

  6. TMT One-Stop Shop: From Reliable Sample Preparation to Computational Analysis Platform

    • Mehdi Mirzaei, Dana Pascovici, Jemma X. Wu, Joel Chick, Yunqi Wu, Brett Cooke et al.
    Pages 45-66

  7. Unassigned MS/MS Spectra: Who Am I?

    • Mohashin Pathan, Monisha Samuel, Shivakumar Keerthikumar, Suresh Mathivanan
    Pages 67-74

  8. Methods to Calculate Spectrum Similarity

    • Şule Yilmaz, Elien Vandermarliere, Lennart Martens
    Pages 75-100

  9. Proteotypic Peptides and Their Applications

    • Shivakumar Keerthikumar, Suresh Mathivanan
    Pages 101-107

  10. Statistical Evaluation of Labeled Comparative Profiling Proteomics Experiments Using Permutation Test

    • Hien D. Nguyen, Geoffrey J. McLachlan, Michelle M. Hill
    Pages 109-117

  11. De Novo Peptide Sequencing: Deep Mining of High-Resolution Mass Spectrometry Data

    • Mohammad Tawhidul Islam, Abidali Mohamedali, Criselda Santan Fernandes, Mark S. Baker, Shoba Ranganathan
    Pages 119-134

  12. Phylogenetic Analysis Using Protein Mass Spectrometry

    • Shiyong Ma, Kevin M. Downard, Jason W. H. Wong
    Pages 135-146

  13. Bioinformatics Methods to Deduce Biological Interpretation from Proteomics Data

    • Krishna Patel, Manika Singh, Harsha Gowda
    Pages 147-161

  14. A Systematic Bioinformatics Approach to Identify High Quality Mass Spectrometry Data and Functionally Annotate Proteins and Proteomes

    • Mohammad Tawhidul Islam, Abidali Mohamedali, Seong Beom Ahn, Ishmam Nawar, Mark S. Baker, Shoba Ranganathan
    Pages 163-176

  15. Network Tools for the Analysis of Proteomic Data

    • David Chisanga, Shivakumar Keerthikumar, Suresh Mathivanan, Naveen Chilamkurti
    Pages 177-197

  16. Determining the Significance of Protein Network Features and Attributes Using Permutation Testing

    • Joseph Cursons, Melissa J. Davis
    Pages 199-208

  17. Bioinformatics Tools and Resources for Analyzing Protein Structures

    • Jason J. Paxman, Begoña Heras
    Pages 209-220

  18. In Silico Approach to Identify Potential Inhibitors for Axl-Gas6 Signaling

    • Swathik Clarancia Peter, Jayakanthan Mannu, Premendu P. Mathur
    Pages 221-229

  19. Back Matter

    Pages 231-233
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Keywords

About this book

This 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.

Editors and Affiliations

  • Department of Biochemistry and Genetics, La Trobe Institute for Molecular Science, La Trobe University, Melbourne, Australia

    Shivakumar Keerthikumar, Suresh Mathivanan

Bibliographic Information

  • Book Title: Proteome Bioinformatics

  • Editors: Shivakumar Keerthikumar, Suresh Mathivanan

  • Series Title: Methods in Molecular Biology

  • DOI: https://doi.org/10.1007/978-1-4939-6740-7

  • Publisher: Humana New York, NY

  • eBook Packages: Springer Protocols

  • Copyright Information: Springer Science+Business Media LLC 2017

  • Hardcover ISBN: 978-1-4939-6738-4Published: 15 December 2016

  • Softcover ISBN: 978-1-4939-8288-2Published: 07 July 2018

  • eBook ISBN: 978-1-4939-6740-7Published: 14 December 2016

  • Series ISSN: 1064-3745

  • Series E-ISSN: 1940-6029

  • Edition Number: 1

  • Number of Pages: XI, 233

  • Number of Illustrations: 11 b/w illustrations, 40 illustrations in colour

  • Topics: Bioinformatics

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