Mathematical Sciences: Spatial Stochastic Models in Biology; May 26-28, 1994; Colorado Springs, Colorado

9312348 Schinazi这里提议的会议将汇集一批对将概率模型应用于生物学感兴趣的杰出生物学家和数学家。最近，在理解一些相互作用的粒子系统（马尔可夫空间随机模型）和一类传统上用于模拟生态系统的微分方程之间的相互作用方面取得了重大进展。随机模型扩展了传统的确定性生物学模型，并为概率学家和生物学家开辟了新的问题。事实上，一个新的视角和立足点已经获得了在这个建立良好的数学建模领域，承诺相当富有成效。一方面，更广泛的观点可以用来证明生物学家所做的各种模拟，并为模拟提供新的思路，而另一方面，它提出了一些关于新的随机模型的有趣的概率问题。最近研究人员在相互作用粒子系统和数学生物学方面的合作表明，过去所做的随机生物模型的分析有时可以用现代概率观点来澄清。从这个新的角度来看，数学生物学家和生态学家引入的原始随机模型除了提出了许多重要的生物学新见解外，还获得了统一的意义。这次会议代表了一个独特的机会，在一个统一的论坛上推进数学生物学，概率论，生态学和流行病学。＊＊＊

9312348 Schinazi The conference proposed here will bring together a group of outstanding biologist and mathematicians who are interested in applying Probability models to Biology. Recently there have been significant advances in understanding the interplay between some interacting particle systems (Markovian spatial stochastic models) and the class of differential equations traditionally used to model ecological systems. The stochastic models extend the traditional deterministic biological models and open new issues for probabilists and biologists alike. Indeed a fresh perspective and foothold has been gained in this well established area of mathematical modelling which promises to quite fruitful. On the one hand the broader view may be used to justify various simulations done by biologist as well as give new ideas for simulations, while on the other hand it raises several interesting probability questions about new stochastic models. Recent collaboration between researchers in interacting particle systems and mathematical biology has shown that analyses of stochastic biological models which have been done in the past can sometimes be clarified using the modern probablilisitic viewpoint. Seen from this new light, the original stochastic models introduced by mathematical biologist and ecologists acquire a unified meaning besides presenting a number of important new biological insights. This conference represents a unique opportunity to advance mathematical biology, probability, ecology, and epidemiology in a unified forum. ***