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Cancer Bioinformatics

  • Book
  • © 2014

Overview

  • 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

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Table of contents (14 chapters)

Keywords

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.

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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