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Timothy D. Veenstra - Proteomic Applications in Cancer Detection and Discovery - 9780471724063 - V9780471724063
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Proteomic Applications in Cancer Detection and Discovery

€ 103.08
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Description for Proteomic Applications in Cancer Detection and Discovery Hardcover. Bridging the knowledge gap between scientists that develop and apply proteomics technologies and oncologists who focus on understanding the biological basis behind cancer manifestation and progression, this title provides an account of how the multiple facets of proteomics have been applied to cancer. Num Pages: 320 pages, illustrations. BIC Classification: MBGR; MJCL; PSBC. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 242 x 160 x 21. Weight in Grams: 566.

Helps researchers in proteomics and oncology work together to understand, prevent, and cure cancer

Proteomic data is increasingly important to understanding the origin and progression of cancer; however, most oncologic researchers who depend on proteomics for their studies do not collect the data themselves. As a result, there is a knowledge gap between scientists, who devise proteomic techniques and collect the data, and the oncologic researchers, who are expected to interpret and apply proteomic data. Bridging the gap between proteomics and oncology research, this book explains how proteomic technology can be used to address some of the most important questions ... Read more

Proteomic Applications in Cancer Detection and Discovery enables readers to understand how proteomic data is acquired and analyzed and how it is interpreted. Author Timothy Veenstra has filled the book with examples—many based on his own firsthand research experience—that clearly demonstrate the application of proteomic technology in oncology research, including the discovery of novel biomarkers for different types of cancers.

The book begins with a brief introduction to systems biology, explaining why cancer is a systems biology disease. Next, it covers such topics as:

  • Mass spectrometry in cancer research
  • Application of proteomics to global phosphorylation analysis
  • Search for biomarkers in biofluids
  • Rise and fall of proteomic patterns for cancer diagnostics
  • Emergence of protein arrays
  • Role of proteomics in personalized medicine

The final chapter is dedicated to the future prospects of proteomics in cancer research.

By guiding readers through the latest proteomic technologies and their applications in cancer research, Proteomic Applications in Cancer Detection and Discovery enhances the ability of researchers in proteomics and researchers in oncology to collaborate in order to better understand cancer and develop strategies to prevent and treat it.

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Product Details

Format
Hardback
Publication date
2013
Publisher
John Wiley and Sons Ltd United Kingdom
Number of pages
320
Condition
New
Number of Pages
320
Place of Publication
New York, United States
ISBN
9780471724063
SKU
V9780471724063
Shipping Time
Usually ships in 7 to 11 working days
Ref
99-18

About Timothy D. Veenstra
TIMOTHY D. VEENSTRA, PhD, is Director of the Laboratory of Proteomics and Analytical Technologies at the Frederick National Laboratory for Cancer Research. Dr. Veenstra and his lab group develop and apply chromatography and mass spectrometry approaches to characterize protein complexes and the role of post-translational modifications in these complexes. Additionally, they use high-throughput proteomic approaches for the discovery of biomarkers ... Read more

Reviews for Proteomic Applications in Cancer Detection and Discovery
“By guiding readers through the latest proteomic technologies and their applications in cancer research, “Proteomic Applications in Cancer Detection and Discovery" enhances the ability of researchers in proteomics and researchers in oncology to collaborate in order to better understand cancer and develop strategies to prevent and treat it.”  (Newbooks.lib, 11 September 2014

Goodreads reviews for Proteomic Applications in Cancer Detection and Discovery


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