Collective Behavior In Systems Biology A Primer on Modeling Infrastructure

Langue : Anglais

Auteur : Steinschneider Assaf

Couverture de l’ouvrage Collective Behavior In Systems Biology

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Collective Behavior In Systems Biology: A Primer on Modeling Infrastructure offers a survey of established and emerging methods for quantifying process behavior in cellular systems. It introduces and applies mathematics and related abstract methods to processes in biological systems - why they are used, how they work, and what they mean. Emphasizing differential equations in an interdisciplinary approach, this book discusses infrastructure for kinetic modeling, technological system and control theories, optimization, and process behavior in cellular networks. The knowledge that the reader gains will be valuable for entering and keeping up with a rapidly developing discipline.

1. Change/differential equations2. Consensus/linear algebra3. Alternative infrastructure/series, numerical methods4. Systems/input into output5. Managing processes/control6. Best choices/optimization7. Chance encounters/random processes8. Organized behavior/networks

: graduate students in systems biology; researchers with biological/biomedical background willing to learn computational modelling

Since childhood Dr. Steinschneider had been interested in general biology and chemistry, later on focusing more on plant and microbiology, genetics, and especially biochemistry. Having earned a BSc in agriculture and a PhD in molecular biology, his professional life was centered on research in a wide range of molecular life sciences at leading research universities in the United States and abroad where he also taught undergraduate- and graduate-level courses. His interests were in the infrastructure for investigating collective behavior in cellular systems and their processes.

Introduces basics of mathematical and abstract methods for understanding, predicting, and modifying collective behavior in cellular systems
Targets biomedical professionals as well as computational specialists who are willing to take advantage of novel high-throughput data acquisition technologies