Authors:
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)
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Front Matter
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Back Matter
About this book
Authors and Affiliations
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Department of Biochemistry and Molecular Biology, University of Georgia, Athens, USA
Ying Xu, David Puett
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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