E-Book, Englisch, 456 Seiten
Reihe: Chapman & Hall/CRC Mathematical & Computational Biology
Wang Cancer Systems Biology
1. Auflage 2010
ISBN: 978-1-4398-1186-3
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)
E-Book, Englisch, 456 Seiten
Reihe: Chapman & Hall/CRC Mathematical & Computational Biology
ISBN: 978-1-4398-1186-3
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)
The unprecedented amount of data produced with high-throughput experimentation forces biologists to employ mathematical representation and computation methods to glean meaningful information in systems-level biology. Applying this approach to the underlying molecular mechanisms of tumorigenesis, cancer researchers can uncover a series of new discoveries and biological insights.
The First Cancer Systems Biology Book Designed for Computational and Experimental Biologists
Unusual in its dualistic approach, Cancer Systems Biology discusses the recent progress in the understanding of cancer systems biology at a time when more and more researchers and pharmaceutical companies are looking into a systems biology approach to find drugs that can effectively be used to treat cancer patients.
Includes Contributions from more than 30 International Experts
Part I introduces basic concepts and theories of systems biology and their applications in cancer research, including case studies of current efforts in cancer systems biology. Part II discusses basic cancer biology and cutting-edge topics of cancer research for computational biologists. In contains an overview of genomics, cell signaling, and tumorigenesis, in addition to hot topics like molecular mechanisms of cancer metastasis and the molecular relationships between solid tumors, their microenvironments, and tumor blood vessels. Rounding out the book’s solid coverage, Part III explores a variety of computational tools and public data resources that are useful for studying cancer problems at a systems level.
Cancer systems biology is still in its infancy as a field of study, but it is fast becoming indispensable in the battle to defeat cancer and develop successful new treatments. Cancer Systems Biology marks an important step toward reaching that goal.
Zielgruppe
Graduate students and researchers in bioinformatics and computational biology and systems biology researchers interested in cancer from life sciences, biophysics, biochemistry, and biomedical engineering.
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Foreword
Hiroaki Kitano, President, The Systems Biology Institute, Tokyo, Japan
CANCER SYSTEMS BIOLOGY: CONCEPTS AND APPLICATIONS
A Roadmap of Cancer Systems Biology
Edwin Wang
Network Biology, the Framework of Systems Biology
Jing-Dong Han
Reconstructing Gene Networks Using Gene Expression Profiles
Mario Lauria and Diego di Bernardo
Understanding Cancer Progression in Protein Interaction Networks
Jinsheng Sun, Jie Li, and Edwin Wang
From Tumor Genome Sequencing to Cancer Signaling Maps
Cong Fu and Edwin Wang
Ubiquitin-Mediated Regulation of Human Signaling Networks in Normal and Cancer Cells
Cong Fu, Jie Li, and Edwin Wang
microRNA Regulation of Networks of Normal and Cancer Cells
Pradeep Kumar Shreenivasaiah, Do Han Kim, and Edwin Wang
Network Model of Survival Signaling in T-Cell Large Granular Lymphocyte Leukemia
Ranran Zhang, Thomas P. Loughran, Jr., and Réka Albert
Cancer Metabolic Networks: Metabolic Pathways Modeling and Metabolomics in Cancer Research
Miroslava Cuperlovic-Culf
Warburg Revisited: Modeling Energy Metabolism for Cancer Systems Biology
Mathieu Cloutier
Cancer Gene Prediction Using a Network Approach
Xuebing Wu and Shao Li
CANCER BIOLOGY: BASIC CONCEPTS AND CUTTING-EDGE TOPICS
Cancer Genomics to Cancer Biology
Maria Luz Jaramillo and Chabane Tibiche
Epithelial-to-Mesenchymal Transition (EMT): The Good, the Bad, and the Ugly
Anne E.G. Lenferink
Tumors and Their Microenvironments
Nicholas R. Bertos and Morag Park
Tumor Angiogenesis: Cell-Microenvironment Interactions
Ally Pen, Danica B. Stanimirovic, Maria J. Moreno
DATA RESOURCES AND SOFTWARE TOOLS FOR CANCER SYSTEMS BIOLOGY
Modeling Tools for Cancer Systems Biology
Wayne Materi and David S. Wishart
Advanced Visualization, Analysis and Inference of Biological Networks Using VisANT
Zhenjun Hu
Gene Set and Pathway-Based Analysis for Cancer Omics
Dougu Nam and Seon-Young Kim
SH2 Domain Signaling Network and Cancer
Shawn S.-C. Li and Thamara K.J. Dayarathna
Data Sources and Computational Tools for Cancer Systems Biology
Yun Ma, Pradeep Kumar Shreenivasaiah, and Edwin Wang