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Informatics In Proteomics [Pehme köide]

  • Formaat: Paperback / softback, 436 pages, kõrgus x laius: 234x156 mm, kaal: 920 g
  • Ilmumisaeg: 23-Oct-2019
  • Kirjastus: CRC Press
  • ISBN-10: 0367392550
  • ISBN-13: 9780367392550
Teised raamatud teemal:
  • Formaat: Paperback / softback, 436 pages, kõrgus x laius: 234x156 mm, kaal: 920 g
  • Ilmumisaeg: 23-Oct-2019
  • Kirjastus: CRC Press
  • ISBN-10: 0367392550
  • ISBN-13: 9780367392550
Teised raamatud teemal:
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 research and analysis.

Through computer simulations, scientists can determine more about how diseases affect cells, predict how various drug interventions would work, and ultimately use proteins as therapeutic targets. This book first addresses the infrastructure needed for public protein databases. It discusses information management systems and user interfaces for storage, retrieval, and visualization of the data as well as issues surrounding data standardization and integration of protein sequences recorded in the last two decades. The authors subsequently examine the application of statistical and bioinformatic tools to data analysis, data presentation, and data mining. They discuss the implementation of algorithms, statistical methods, and computer applications that facilitate pattern recognition and biomarker discovery by integrating data from multiple sources.

This book offers a well-rounded resource of informatic approaches to data storage, retrieval, and protein analysis as well as application-specific bioinformatic tools that can be used in disease detection, diagnosis, and treatment. Informatics in Proteomics captures the current state-of-the-art and provides a valuable foundation for future directions.
Chapter 1 The Promise of Proteomics: Biology, Applications, and Challenges
1(16)
Paul D. Wagner
Sudhir Srivastava
Chapter 2 Proteomics Technologies and Bioinformatics
17(14)
Sudhir Srivastava
Mukesh Verma
Chapter 3 Creating a National Virtual Knowledge Environment for Proteomics and Information Management
31(22)
Daniel Crichton
Heather Kincaid
Sean Kelly
Sudhir Srivastava
J. Steven Hughes
Donald Johnsey
Chapter 4 Public Protein Databases and Interfaces
53(26)
Jane Meejung Chang Oh
Chapter 5 Proteomics Knowledge Databases: Facilitating Collaboration and Interaction between Academia, Industry, and Federal Agencies
79(30)
Denise B. Warzel
Marcy Winget
Cim Edelstein
Chenwei Lin
Mark Thornquist
Chapter 6 Proteome Knowledge Bases in the Context of Cancer
109(32)
Djamel Medjahed
Peter A. Lemkin
Chapter 7 Data Standards in Proteomics: Promises and Challenges
141(22)
Veerasamy Ravichandran
Ram D. Sriram
Gary L. Gilliland
Sudhir Srivastava
Chapter 8 Data Standardization and Integration in Collaborative Proteomics Studies
163(30)
Marcin Adamski
David J. States
Gilbert S. Omenn
Chapter 9 Informatics Tools for Functional Pathway Analysis Using Genomics and Proteomics
193(12)
Chad Creighton
Samir M. Hanash
Chapter 10 Data Mining in Proteomics
205(22)
R. Gangal
Chapter 11 Protein Expression Analysis
227(28)
Guoan Chen
David G. Beer
Chapter 12 Nonparametric, Distance-Based, Supervised Protein Array Analysis
255(12)
Mei-Fen Yeh
Jeanne Kowalski
Nicole White
Zhen Zhang
Chapter 13 Protein Identification by Searching Collections of Sequences with Mass Spectrometric Data
267(10)
D. Fenyo
J. Eriksson
R.C. Beavis
Chapter 14 Bioinformatics Tools for Differential Analysis of Proteomic Expression Profiling Data from Clinical Samples
277(16)
Zhen Zhang
Chapter 15 Sample Characterization Using Large Data Sets
293(42)
Brian T. Luke
Chapter 16 Computational Tools for Tandem Mass Spectrometry-Based High-Throughput Quantitative Proteomics
335(18)
Jimmy K. Eng
Andrew Keller
Xiao-jun Li
Alexey I. Nesvizhskii
Ruedi Aebersold
Chapter 17 Pattern Recognition Algorithms and Disease Biomarkers
353(14)
Ben A. Hitt
Emanuel Petricoin
Lance Liotta
Chapter 18 Statistical Design and Analytical Strategies for Discovery of Disease-Specific Protein Patterns
367(24)
Ziding Feng
Yutaka Yasui
Dale McLerran
Bao-Ling Adam
John Semmes
Chapter 19 Image Analysis in Proteomics
391(42)
Stephen Lockett
Index 433
Sudhir Srivastava