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Jump down to see edition details for: Hardcover
Bibliographic Detail
Publisher
Springer-Verlag New York Inc
Publication date
September 1, 2014
Binding
Hardcover
Book category
Adult Non-Fiction
ISBN-13
9781493913800
ISBN-10
1493913808
Dimensions
1 by 6.50 by 9.50 in.
Weight
1.50 lbs.
Original list price
$129.00
Amazon.com says people who bought this book also bought:
Bioinformatics Algorithms An Active Learning Approach | Statistical Analysis of Next Generation Sequencing Data | RNA-seq Data Analysis | Primer to Analysis of Genomic Data Using R
Bioinformatics Algorithms An Active Learning Approach | Statistical Analysis of Next Generation Sequencing Data | RNA-seq Data Analysis | Primer to Analysis of Genomic Data Using R
Summaries and Reviews
Amazon.com description: Product Description: 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.
Editions
Hardcover
The price comparison is for this edition
9781493913800 | details & prices | 6.50 × 9.50 × 1.00 in. | 1.50 lbs | List price $129.00
About: This book provides a framework for computational researchers studying the basics of cancer through comparative analyses of omic data.
About: This book provides a framework for computational researchers studying the basics of cancer through comparative analyses of omic data.
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