Cancer Bioinformatics

Nonfiction, Health & Well Being, Medical, Specialties, Oncology, Computers, Advanced Computing, Computer Science, Science & Nature, Science
Cover of the book Cancer Bioinformatics by Ying Xu, Juan Cui, David Puett, Springer New York
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Author: Ying Xu, Juan Cui, David Puett ISBN: 9781493913817
Publisher: Springer New York Publication: August 30, 2014
Imprint: Springer Language: English
Author: Ying Xu, Juan Cui, David Puett
ISBN: 9781493913817
Publisher: Springer New York
Publication: August 30, 2014
Imprint: Springer
Language: English

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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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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