Proteome Bioinformatics

Suresh Mathivanan

ISBN 10: 149396738X / ISBN 13: 9781493967384

Edité par Springer New York, Springer US Dez 2016, 2016

A propos de cet article

Neuware -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.Humana Press in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 248 pp. Englisch.

N° de réf. du vendeur 9781493967384

Détails bibliographiques

• Titre: Proteome Bioinformatics
• Éditeur: Springer New York, Springer US Dez 2016
• Date de parution: 2016
• Langue: anglais
• ISBN à 10 chiffres: 149396738X
• ISBN à 13 chiffres: 9781493967384
• Reliure: Buch
• État de l'article: Neu

A propos de ce titre

Synopsis

1. An Introduction to Proteome Bioinformatics

Shivakumar Keerthikumar

2. Proteomic Data Storage and Sharing

Shivakumar Keerthikumar and Suresh Mathivanan

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

Dhirendra Kumar, Amit Kumar Yadav, and Debasis Dash

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

Sushma Anand, Monisha Samuel, Ching-Seng Ang, Shivakumar Keerthikumar, and Suresh Mathivanan

5. 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, Paul Haynes, and Mark P. Molloy

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

Mohashin Pathan, Monisha Samuel, Shivakumar Keerthikumar, and Suresh Mathivanan

7. Methods to Calculate Spectrum Similarity

Şule Yılmaz, Elien Vandermarliere, and Lennart Martens

8. Proteotypic Peptides and Their Applications

Shivakumar Keerthikumar and Suresh Mathivanan

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

Hien D. Nguyen, Geoffrey J. McLachlan, and Michelle M. Hill

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

Mohammad Tawhidul Islam, Abidali Mohamedali, Criselda Santan Fernandes, Mark S. Baker, and Shoba Ranganathan

11. Phylogenetic Analysis Using Protein Mass Spectrometry

Shiyong Ma, Kevin M. Downard, and Jason W.H. Wong

12. Bioinformatics Methods to Deduce Biological Interpretation from Proteomics Data

Krishna Patel, Manika Singh, and Harsha Gowda

13. 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, and Shoba Ranganathan

14. Network Tools for the Analysis of Proteomic Data

David Chisanga, Shivakumar Keerthikumar, Suresh Mathivanan, and Naveen Chilamkurti

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

Joseph Cursons and Melissa J. Davis

16. Bioinformatics Tools and Resources for Analyzing Protein Structures

Jason J. Paxman and Begoña Heras

17. In Silico Approach to Identify Potential Inhibitors for Axl-Gas6 Signalling