Bioinformatics for Comparative Proteomics
Published on 19. November 2010
Book
Hardback
XIII, 387 pages
978-1-60761-976-5 (ISBN)
Description
With the rapid development of proteomic technologies in the life sciences and in clinical applications, many bioinformatics methodologies, databases, and software tools have been developed to support comparative proteomics study. In Bioinformatics for Comparative Proteomics, experts in the field highlight the current status, challenges, open problems, and future trends for developing bioinformatics tools and resources for comparative proteomics research in order to deliver a definitive reference providing both the breadth and depth needed on the subject. Structured in three major sections, this detailed volume covers basic bioinformatics frameworks relating to comparative proteomics, bioinformatics databases and tools for proteomics data analysis, and integrated bioinformatics systems and approaches for studying comparative proteomics in the systems biology context. Written for the highly successful Methods in Molecular BiologyT series, the contributions in this book provide the meticulous, step-by-step description and implementation advice that is crucial for getting optimal results in the lab.
Comprehensive and easy-to-use, Bioinformatics for Comparative Proteomics serves all readers who wish to learn about state-of-the-art bioinformatics databases and tools, novel computational methods and future trends in proteomics data analysis, and comparative proteomics in systems biology.
Reviews / Votes
From the reviews:
"This book provides comprehensive coverage of the current status, challenges, open problems, and future trends in developing bioinformatics tools and resources for comparative proteomics research. . The audience ranges from graduate students embarking upon a research project to practicing biologists and bioinformaticians. This broad audience working in biotechnology and pharmaceutical companies and in various academic departments . will find this book quite useful. . This well-illustrated book is a comprehensive resource on bioinformatics for comparative proteomics." (Omer Iqbal, Doody's Book Reviews, March, 2012)More details
Series
Edition
2011
Language
English
Place of publication
Totowa
United States
Target group
Professional and scholarly
Professional/practitioner
Illustrations
XIII, 387 p.
Dimensions
Height: 260 mm
Width: 183 mm
Thickness: 27 mm
Weight
954 gr
ISBN-13
978-1-60761-976-5 (9781607619765)
DOI
10.1007/978-1-60761-977-2
Schweitzer Classification
Other editions
Additional editions
Cathy H. Wu | Chuming Chen
Bioinformatics for Comparative Proteomics
Book
08/2016
Humana Press Inc.
€117.69
Shipment within 15-20 days
Content
Protein Bioinformatics Databases and Resources.- A Guide to UniProt for Protein Scientists.- InterPro Protein Classification.- Reactome Knowledgebase of Human Biological Pathways and Processes.- eFIP: A Tool for Mining Functional Impact of Phosphorylation from Literature.- A Tutorial on Protein Ontology Resources for Proteomic Studies.- Structure-Guided Rule-Based Annotation of Protein Functional Sites in UniProt Knowledgebase.- Modeling Mass Spectrometry-Based Protein Analysis.- Protein Identification from Tandem Mass Spectra by Database Searching.- LC-MS Data Analysis for Differential Protein Expression Detection.- Protein Identification by Spectral Networks Analysis.- Software Pipeline and Data Analysis for MS/MS Proteomics: The Trans-Proteomic Pipeline.- Analysis of High-Throughput ELISA Microarray Data.- Proteomics Databases and Repositories.- Preparing Molecular Interaction Data for Publication.- Submitting Proteomics Data to PRIDE Using PRIDE Converter
Automated Data Integrationand Determination of Posttranslational Modi?cations with the Protein Inference Engine.- An Integrated Top-Down and Bottom-Up Strategy for Broadly Characterizing Protein Isoforms and Modifications.- Phosphoproteome Resource for Systems Biology Research.- Protein-Centric Data Integration for Functional Analysis of Comparative Proteomics Data.- Integration of Proteomic and Metabolomic Profiling as well as Metabolic Modeling for the Functional Analysis of Metabolic Networks.- Time Series Proteome Profiling.