Proteome Bioinformatics - (Methods in Molecular Biology) by Shivakumar Keerthikumar & Suresh Mathivanan (Hardcover)
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<p/><br></br><p><b> Book Synopsis </b></p></br></br><p><b>1. An Introduction to Proteome Bioinformatics</b></p> <p> Shivakumar Keerthikumar</p> <p> </p> <p><b>2. Proteomic Data Storage and Sharing</b></p> <p> Shivakumar Keerthikumar and Suresh Mathivanan</p> <p> </p> <p><b>3. Choosing an Optimal Database for Protein Identification from Tandem Mass Spectrometry Data</b></p> <p> Dhirendra Kumar, Amit Kumar Yadav, and Debasis Dash</p> <p> </p> <p><b>4. Label-Based and Label-Free Strategies for Protein Quantitation</b></p> Sushma Anand, Monisha Samuel, Ching-Seng Ang, Shivakumar Keerthikumar, and Suresh Mathivanan</p> <p> </p> <p><b>5. TMT One Stop Shop: From Reliable Sample Preparation to Computational Analysis Platform</b></p> <p> Mehdi Mirzaei, Dana Pascovici, Jemma X. Wu, Joel Chick, Yunqi Wu, Brett Cooke, Paul Haynes, and Mark P. Molloy</p> <p> </p> <p><b>6. Unassigned MS/MS Spectra: Who Am I?</b></p> <p> Mohashin Pathan, Monisha Samuel, Shivakumar Keerthikumar, and Suresh Mathivanan</p> <p> </p> <p><b>7. Methods to Calculate Spectrum Similarity</p> <p> Şule Yılmaz, Elien Vandermarliere, and Lennart Martens</p> <p> </p> <p><b>8. Proteotypic Peptides and Their Applications</b></p> <p> Shivakumar Keerthikumar and Suresh Mathivanan</p> <p> </p> <p><b>9. Statistical Evaluation of Labeled Comparative Profiling Proteomics Experiments Using Permutation Test</b></p> <p> Hien D. Nguyen, Geoffrey J. McLachlan, and Michelle M. Hill</p> <p> </p> <p><b>10. </b><b>De Novo Peptide Sequencing: Deep Mining of High-Resolution Mass Spectrometry Data</b></p> <p> Mohammad Tawhidul Islam, Abidali Mohamedali, Criselda Santan Fernandes, Mark S. Baker, and Shoba Ranganathan</p> <p> </p> <p><b>11. Phylogenetic Analysis Using Protein Mass Spectrometry</b></p> <p> Shiyong Ma, Kevin M. Downard, <sup> </sup>and Jason W.H. Wong</p> <p> </p> <p><b>12. Bioinformatics Methods to Deduce Biological Interpretation from Proteomics Data</b></p> <p> Krishna Patel, Manika Singh, and Harsha Gowda</p> <p> </p> <p><b>13. A Systematic Bioinformatics Approach to Identify High Quality Mass Spectrometry Data and Functionally Annotate Proteins and Proteomes</b></p> <p> Mohammad Tawhidul Islam, Abidali Mohamedali, Seong Beom Ahn, Ishmam Nawar, Mark S. Baker, and Shoba Ranganathan</p> <p> </p> <p><b>14. Network Tools for the Analysis of Proteomic Data</b></p> <p> David Chisanga, Shivakumar Keerthikumar, Suresh Mathivanan, and Naveen Chilamkurti</p> <p> </p> <p><b>15. Determining the Significance of Protein Network Features and Attributes Using Permutation Testing</b></p> Joseph Cursons and Melissa J. Davis</p> <p> </p> <p><b>16. Bioinformatics Tools and Resources for Analyzing Protein Structures</b></p> <p> Jason J. Paxman and Begoña Heras</p> <p> </p> <p><b>17. In Silico<i> </i>Approach to Identify Potential Inhibitors for Axl-Gas6 Signalling</b></p> <p><p/><br></br><p><b> From the Back Cover </b></p></br></br>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 <i>Methods in Molecular Biology </i>series, chapters contain the kind of detail and key implementation advice to ensure successful results. <br>Authoritative and cutting-edge, <i>Proteome Bioinformatics</i> serves as a useful resource for researchers who are beginners as well as advanced investigators in the field of proteomics.
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