This book demonstrates the power of mathematical thinking in understanding the biological complexity that exists within the brain. It looks at the latest research on modelling of biochemical pathways within synapses, and provides a clear background for the study of mathematical models related to systems biology. Discussion then focusses on developments in computational models based on networks linked to synaptic plasticity. The models are used to understand memory formation and impairment and they provide a mathematical basis for memory research.
Computational Systems Biology of Synaptic Plasticity is a valuable source of knowledge to postgraduate students and researchers in computational systems biology, and as a reference book for various techniques that are needed in modelling biological processes.
Readership: Postgraduate students and researchers in computational systems biology, and as a reference book for various techniques that are needed in modelling biological processes.
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Professor Don Kulasiri obtained his PhD related to Bioengineering from Virginia Tech, Blacksburg, USA. He had been a visiting academic to Stanford University, Princeton University, USA, and has been visiting Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, UK, regularly since 2008. He is the professor of Computational Modelling and Systems Biology, a personal Chair, at Lincoln University, Christchurch, New Zealand since 1999. He founded and directs the Centre for Advanced Computational Solutions (C-fACS) at Lincoln since 1999. He is a fellow of the Modelling and Simulation Society of Australia and New Zealand (MSSANZ).
Dr Yao He obtained his PhD in Computational Systems Biology at Lincoln University, New Zealand, and he also has Bachelor of Science degree in Computer Science and Mathematics from University of Canterbury, New Zealand. He has been engaged in systems biology research since 2010, and works as a research scientist in the Centre for Advanced Computational Solutions (C-fACS). His expertise is on modelling the mechanisms of synaptic plasticity, parameter sensitivity analysis and stochastic modelling. His current research focuses on understanding the linkage between presynaptic release and postsynaptic plasticity using stochastic modelling.
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