Informatics In Proteomics
The handling and analysis of data generated by proteomics investigations represent a challenge for computer scientists, biostatisticians, and biologists to develop tools for storing, retrieving, visualizing, and analyzing genomic data. Informatics in Proteomics examines the ongoing advances in the application of bioinformatics to proteomics researc
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Informatics In Proteomics
The handling and analysis of data generated by proteomics investigations represent a challenge for computer scientists, biostatisticians, and biologists to develop tools for storing, retrieving, visualizing, and analyzing genomic data. Informatics in Proteomics examines the ongoing advances in the application of bioinformatics to proteomics researc
84.99 In Stock
Informatics In Proteomics

Informatics In Proteomics

by Sudhir Srivastava (Editor)
Informatics In Proteomics

Informatics In Proteomics

by Sudhir Srivastava (Editor)

eBook

$84.99 

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Overview

The handling and analysis of data generated by proteomics investigations represent a challenge for computer scientists, biostatisticians, and biologists to develop tools for storing, retrieving, visualizing, and analyzing genomic data. Informatics in Proteomics examines the ongoing advances in the application of bioinformatics to proteomics researc

Product Details

ISBN-13: 9781040205051
Publisher: CRC Press
Publication date: 06/24/2005
Sold by: Barnes & Noble
Format: eBook
Pages: 436
File size: 20 MB
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Table of Contents

The Promise of Proteomics: Biology, Applications, and Challenges; Proteomics Technologies; Creating a National Virtual Knowledge Environment for Proteomics and Information Management; Public Protein Databases and Interfaces; Proteomics Knowledge Databases: Facilitating Collaboration and Interaction between Academia, Industry, and Federal Agencies; Proteome Knowledge Bases in the Context of Cancer; Data Standards in Proteomics: Promises and Challenges; Data Standardization and Integration in Collaborative Proteomics Studies; Informatics Tools for Functional Pathway Analysis Using Genomics and Proteomics; Data Mining in Proteomics; Protein Expression Analysis; Nonparametric, Distance-Based, Supervised Protein Array Analysis; Protein Identification by Searching Collection of Sequences with Mass Spectrometric Data; Bioinformatics Tools for Differential Analysis of Proteomic Expression Profiling Data from Clinical Samples; Sample Characterization Using Large Data Sets; Computational Tools for Tandem Mass Spectrometry-Based High-Throughput Quantitative Proteomics; Pattern Recognition Algorithms and Disease Biomarkers; Statistical Design and Analytical Strategies for Discovery of Disease-Specific Protein Patterns; Image Analysis in Proteomics; Index
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