统计 | Guide to Simulation and Modeling for Biosciences

作者:阁楼君

The philosophy of this book, therefore, is to discuss both aspects—the technical side and the side that concerns being able to identify the right degree of abstraction.

Guide to Simulation and Modeling for Biosciences 

Second Edition



David J. Barnes,Dominique Chu



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In this book we seek to provide a detailed introduction to a range of simulation and modeling techniques that are appropriate for use in the biosciences. The book is primarily intended for bioscientists, but will be equally useful for anybody wishing to start simulation and modeling in related fields. The topics we discuss include agent-based models, stochastic modeling techniques, differential equations, and Gillespie’s stochastic simulation algorithm. Throughout, we pay particular attention to the needs of the novice modeler. We recognize that simulation and modeling in science in general (and in biology, in particular) require both skills (i.e., programming, developing algorithms, and solving equations) and techniques (i.e., the ability to recognize what is important and needs to be represented in the model, and what can and should be left out). In our experience with novice modelers we have noticed that: (i) both skill and technique are equally important; and (ii) both are normally lacking to some degree.


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