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北京石油化工学院2026年研究生招生接收调剂公告
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[资源] Cancer Bioinformatics by Ying Xu et al. Springer 2014

Cancer Bioinformatics
by Ying Xu; Juan Cui; David Puett
Springer 2014

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.

Table of contents (14 chapters)
Basic Cancer Biology  Pages 1-39
Omic Data, Information Derivable and Computational Needs  Pages 41-63
Cancer Classification and Molecular Signature Identification  Pages 65-87
Understanding Cancer at the Genomic Level   Pages 89-112
Elucidation of Cancer Drivers Through Comparative Omic Data Analyses  Pages 113-147
Hyaluronic Acid: A Key Facilitator of Cancer Evolution   Pages 149-177
Multiple Routes for Survival: Understanding How Cancer Evades Apoptosis   Pages 179-203
Cancer Development in Competitive and Hostile Environments   Pages 205-227
Cell Proliferation from Regulated to Deregulated States Via Epigenomic Responses   Pages 229-251
Understanding Cancer Invasion and Metastasis   Pages 253-278
Cancer After Metastasis: The Second Transformation   Pages 279-304
Searching for Cancer Biomarkers in Human Body Fluids   Pages 305-326
In Silico Investigation of Cancer Using Publicly Available Data   Pages 327-351
Understanding Cancer as an Evolving Complex System: Our Perspective   Pages 353-362


Cancer Bioinformatics by Ying Xu et al.  Springer 2014
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