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Cancer Bioinformatics

  • Book
  • © 2014

Overview

Authors:
  1. Ying Xu

    1. Department of Biochemistry and Molecular Biology, University of Georgia, Athens, USA

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  2. Juan Cui

    1. Department of Computer Science and Engineering, University of Nebraska, Lincoln, USA

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    You can also search for this author in PubMed   Google Scholar

  3. David Puett

    1. Department of Biochemistry and Molecular Biology, University of Georgia, Athens, USA

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  • Focuses on the understanding of cancer biology from an informatics perspective
  • Provides a unified conceptual framework for studying a variety of cancer related problems by considering cancer a process of cell survival through cell proliferation
  • Teaches hypothesis-driven omic data mining and statistical inference of mechanistic relationships important to cancer initiation, progression, metastasis and post-metastasis development
  • Gives a large collection of examples related to different aspects of cancer study using omic data analyses to answer a wide range of questions
  • Includes supplementary material: sn.pub/extras

  • 37k Accesses

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About this book

This book provides a framework for computational researchers studying the basics of cancer through comparative analyses of omic data. It discusses how key cancer pathways can be analyzed and discovered to derive new insights into the disease and identifies diagnostic and prognostic markers for cancer. Chapters explain the basic cancer biology and how cancer develops, including the many potential survival routes. The examination of gene-expression patterns uncovers commonalities across multiple cancers and specific characteristics of individual cancer types. The authors also treat cancer as an evolving complex system, explore future case studies, and summarize the essential online data sources. Cancer Bioinformatics is designed for practitioners and researchers working in cancer research and bioinformatics. It is also suitable as a secondary textbook for advanced-level students studying computer science, biostatistics or biomedicine.

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Table of contents (14 chapters)

  1. Front Matter

    Pages i-xxvi
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  2. Basic Cancer Biology

    • Ying Xu, Juan Cui, David Puett
    Pages 1-39

  3. Omic Data, Information Derivable and Computational Needs

    • Ying Xu, Juan Cui, David Puett
    Pages 41-63

  4. Cancer Classification and Molecular Signature Identification

    • Ying Xu, Juan Cui, David Puett
    Pages 65-87

  5. Understanding Cancer at the Genomic Level

    • Ying Xu, Juan Cui, David Puett
    Pages 89-112

  6. Elucidation of Cancer Drivers Through Comparative Omic Data Analyses

    • Ying Xu, Juan Cui, David Puett
    Pages 113-147

  7. Hyaluronic Acid: A Key Facilitator of Cancer Evolution

    • Ying Xu, Juan Cui, David Puett
    Pages 149-177

  8. Multiple Routes for Survival: Understanding How Cancer Evades Apoptosis

    • Ying Xu, Juan Cui, David Puett
    Pages 179-203

  9. Cancer Development in Competitive and Hostile Environments

    • Ying Xu, Juan Cui, David Puett
    Pages 205-227

  10. Cell Proliferation from Regulated to Deregulated States Via Epigenomic Responses

    • Ying Xu, Juan Cui, David Puett
    Pages 229-251

  11. Understanding Cancer Invasion and Metastasis

    • Ying Xu, Juan Cui, David Puett
    Pages 253-278

  12. Cancer After Metastasis: The Second Transformation

    • Ying Xu, Juan Cui, David Puett
    Pages 279-304

  13. Searching for Cancer Biomarkers in Human Body Fluids

    • Ying Xu, Juan Cui, David Puett
    Pages 305-326

  14. In Silico Investigation of Cancer Using Publicly Available Data

    • Ying Xu, Juan Cui, David Puett
    Pages 327-351

  15. Understanding Cancer as an Evolving Complex System: Our Perspective

    • Ying Xu, Juan Cui, David Puett
    Pages 353-362

  16. Back Matter

    Pages 363-368
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Authors and Affiliations

  • Department of Biochemistry and Molecular Biology, University of Georgia, Athens, USA

    Ying Xu, David Puett

  • Department of Computer Science and Engineering, University of Nebraska, Lincoln, USA

    Juan Cui

Bibliographic Information

  • Book Title: Cancer Bioinformatics

  • Authors: Ying Xu, Juan Cui, David Puett

  • DOI: https://doi.org/10.1007/978-1-4939-1381-7

  • Publisher: Springer New York, NY

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer Science+Business Media New York 2014

  • Hardcover ISBN: 978-1-4939-1380-0Published: 01 September 2014

  • Softcover ISBN: 978-1-4939-4303-6Published: 17 September 2016

  • eBook ISBN: 978-1-4939-1381-7Published: 30 August 2014

  • Edition Number: 1

  • Number of Pages: XXVI, 368

  • Number of Illustrations: 68 b/w illustrations

  • Topics: Computational Biology/Bioinformatics, Cancer Research, Systems Biology, Biomedicine general

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