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Correlation-based network analysis of cancer metabolism

A new systems biology approach in metabolomics

  • This book presents a pioneering technique for analyzing metabolites
  • Explores the metabolome as the closest entity to the phenotype of a biological system
  • A useful tool for introducing metabolomics to the cancer research community
  • Includes supplementary material: sn.pub/extras

Part of the book series: SpringerBriefs in Systems Biology (BRIEFSBIOSYS)

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Table of contents (6 chapters)

  1. Front Matter

    Pages i-vi
  2. An Overview of Cancer Metabolism

    • Emily G. Armitage, Helen L. Kotze, Kaye J. Williams
    Pages 1-6
  3. Cancer Hypoxia and the Tumour Microenvironment as Effectors of Cancer Metabolism

    • Emily G. Armitage, Helen L. Kotze, Kaye J. Williams
    Pages 7-14
  4. Metabolic Fingerprinting of In Vitro Cancer Cell Samples

    • Emily G. Armitage, Helen L. Kotze, Kaye J. Williams
    Pages 15-20
  5. Network-Based Correlation Analysis of Metabolic Fingerprinting Data

    • Emily G. Armitage, Helen L. Kotze, Kaye J. Williams
    Pages 21-34
  6. Case Study: Systems Biology of HIF Metabolism in Cancer

    • Emily G. Armitage, Helen L. Kotze, Kaye J. Williams
    Pages 35-48
  7. Case Study: Systems Biology of Chemotherapy Resistance in Hypoxic Cancer

    • Emily G. Armitage, Helen L. Kotze, Kaye J. Williams
    Pages 49-61

About this book

With the rise of systems biology as an approach in biochemistry research, using high throughput techniques such as mass spectrometry to generate metabolic profiles of cancer metabolism is becoming increasingly popular. There are examples of cancer metabolic profiling studies in the academic literature; however they are often only in journals specific to the metabolomics community. This book will be particularly useful for post-graduate students and post-doctoral researchers using this pioneering technique of network-based correlation analysis. The approach can be adapted to the analysis of any large scale metabolic profiling experiment to answer a range of biological questions in a range of species or for a range of diseases.

Authors and Affiliations

  • Centre for Metabolomics and Bioanalysis, Universidad San Pablo CEU, Boadilla del Monte, Spain

    Emily G. Armitage

  • University of Manchester Manchester Institute of Biotechnology, Manchester, United Kingdom

    Helen L. Kotze

  • University of Manchester, Manchester Pharmacy School, Manchester Cancer Research Centre, Manchester, United Kingdom

    Kaye J. Williams

Bibliographic Information

  • Book Title: Correlation-based network analysis of cancer metabolism

  • Book Subtitle: A new systems biology approach in metabolomics

  • Authors: Emily G. Armitage, Helen L. Kotze, Kaye J. Williams

  • Series Title: SpringerBriefs in Systems Biology

  • DOI: https://doi.org/10.1007/978-1-4939-0615-4

  • Publisher: Springer New York, NY

  • eBook Packages: Biomedical and Life Sciences, Biomedical and Life Sciences (R0)

  • Copyright Information: The Authors 2014

  • Softcover ISBN: 978-1-4939-0614-7Published: 12 May 2014

  • eBook ISBN: 978-1-4939-0615-4Published: 12 May 2014

  • Series ISSN: 2193-4746

  • Series E-ISSN: 2193-4754

  • Edition Number: 1

  • Number of Pages: VI, 61

  • Number of Illustrations: 7 b/w illustrations, 13 illustrations in colour

  • Topics: Systems Biology, Metabolomics, Cancer Research

Buy it now

Buying options

eBook USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access