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新书推荐： Cancer Bioinformatics

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新书推荐： Cancer Bioinformatics
Xu, Ying, Cui, Juan, Puett, David
2014, XXVI, 368 p. 68 illus.
http://www.springer.com/computer/bioinformatics/book/978-1-4939-1380-0
ABOUT THIS BOOK
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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
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.
Keywords: Bioinformatics - Cancer bioinformatics - Cancer biology - Cancer genomes - Cancer marker identification - Cancer omic data analysis - Cancer pathway analysis - Cancer systems biology - Comparative omic analysis - Computational biology - Omic databases
Chapter list
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1 Basic Cancer Biology
2 Omic Data, Information Derivable and Computational Needs
3 Cancer Classifi cation and Molecular Signature Identifi cation
4 Understanding Cancer at the Genomic Level
5 Elucidation of Cancer Drivers Through Comparative Omic Data Analyses
6 Hyaluronic Acid: A Key Facilitator of Cancer Evolution
7 Multiple Routes for Survival: Understanding How Cancer Evades Apoptosis
8 Cancer Development in Competitive and Hostile Environments
9 Cell Proliferation from Regulated to Deregulated States Via Epigenomic Responses
10 Understanding Cancer Invasion and Metastasis
11 Cancer After Metastasis: The Second Transformation
12 Searching for Cancer Biomarkers in Human Body Fluids
13 In Silico Investigation of Cancer Using Publicly Available Data
14 Understanding Cancer as an Evolving Complex System: Our Perspective