Big Mechanisms in Systems Biology: Big Data Mining, Network Modeling, and Genome-Wide Data Identification - Chen, Bor-Sen (Tsing Hua Distinguished Chair Professor, Department of Electrical Engineering, National Tsing Hua University, Taiwan) - Books - Elsevier Science Publishing Co Inc - 9780128094792 - November 11, 2016
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Big Mechanisms in Systems Biology: Big Data Mining, Network Modeling, and Genome-Wide Data Identification

Chen, Bor-Sen (Tsing Hua Distinguished Chair Professor, Department of Electrical Engineering, National Tsing Hua University, Taiwan)

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Big Mechanisms in Systems Biology: Big Data Mining, Network Modeling, and Genome-Wide Data Identification

"Big Mechanisms in Systems Biology: Big Data Mining, Network Modeling, and Genome-Wide Data Identification explains big mechanisms of systems biology by system identification and big data mining methods using models of biological systems. Systems biology is currently undergoing revolutionary changes in response to the integration of powerful technologies. Faced with a large volume of available literature, complicated mechanisms, small prior knowledge, few classes on the topics, and causal and mechanistic language, this is an ideal resource. This book addresses system immunity, regulation, infection, aging, evolution, and carcinogenesis, which are complicated biological systems with inconsistent findings in existing resources. These inconsistencies may reflect the underlying biology time-varying systems and signal transduction events that are often context-dependent, which raises a significant problem for mechanistic modeling since it is not clear which genes/proteins to include in models or experimental measurements. The book is a valuable resource for bioinformaticians and members of several areas of the biomedical field who are interested in an in-depth understanding on how to process and apply great amounts of biological data to improve research."--


878 pages

Media Books     Paperback Book   (Book with soft cover and glued back)
Released November 11, 2016
ISBN13 9780128094792
Publishers Elsevier Science Publishing Co Inc
Pages 878
Dimensions 191 × 234 × 30 mm   ·   1.34 kg