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21#
發(fā)表于 2025-3-25 03:30:01 | 只看該作者
22#
發(fā)表于 2025-3-25 10:18:14 | 只看該作者
23#
發(fā)表于 2025-3-25 14:51:03 | 只看該作者
Biochemical Models Beyond the Perfect Mixing Assumption,nking about the model. This chapter introduces the reader conceptually to spatial modeling but also contains two walk-through examples. It uses the widely respected Smoldyn simulation software to illustrate the modeling process in spatial systems. The case study in this model is a biochemical change detector.
24#
發(fā)表于 2025-3-25 19:51:08 | 只看該作者
25#
發(fā)表于 2025-3-25 20:18:54 | 只看該作者
Other Stochastic Methods and Prism,. The second part of this chapter describes PRISM, which is a powerful computational tool for formulating, analyzing and simulating Markov-chain models. Throughout the chapter, concepts are illustrated using biologically-motivated case studies.
26#
發(fā)表于 2025-3-26 01:20:32 | 只看該作者
Ana M. Henao,Tatiana Osorio,Aura I. Urrea Java. We illustrate some of the ways in which a toolkit such as Repast considerably simplifies the life of the modeler by providing extensive support for agent creation, model visualization, charting of results, and multiple runs.
27#
發(fā)表于 2025-3-26 04:43:05 | 只看該作者
28#
發(fā)表于 2025-3-26 12:23:02 | 只看該作者
29#
發(fā)表于 2025-3-26 13:57:51 | 只看該作者
30#
發(fā)表于 2025-3-26 18:10:35 | 只看該作者
Agent-Based Modeling,ke systems amenable to ABM modeling. A large part comprises walk through illustrations of two models, namely, the spread of malaria in a spatially structured population and a model of the evolution of fimbriae. This last example also demonstrates how ABMs can be used to simulate evolution in a biologically realistic way.
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