Title: Hybrid stochastic modeling of the budding yeast cell cycle control mechanism

报告人：曹阳

时间：2018年7月2日  11 : 00 - 12 : 00

地点  ：创新研究院813

Abstract:
The budding yeast cell cycle is regulated by complex and multi-scale control mechanisms, and is subject to inherent noise, resulted from low copy numbers of species in a cell. Noise in cellular systems is often modeled and simulated with Gillespie's stochastic simulation algorithm (SSA). However, the low efficiency of SSA limits its application to large practical biochemical networks, which often present multi-scale features in two aspects: species with different scales of abundances and reactions with different scales of firing frequencies.

To improve the efficiency of stochastic simulations, Haseltine and Rawlings (HR) proposed a hybrid algorithm, which combines ordinary differential equations (ODEs) for traditional deterministic models and SSA for stochastic models. In this talk, we will present a comprehensive hybrid model that represents a gene-protein regulatory network of the budding yeast cell cycle control mechanism, respectively, by Gillespie’s stochastic simulation algorithm (SSA) and ordinary differential equations (ODEs). Simulation results of our model are compared with published experimental measurement on the budding yeast cell cycle, which demonstrates that our hybrid model well represents many critical characteristics of the budding yeast cell cycle, and reproduces phenotypes of more than 100 mutant cases. The proposed scheme is considerably faster in both modeling and simulation than the equivalent stochastic simulation. Meanwhile, the accuracy of the HR hybrid method is studied based on a linear chain reaction system.

曹阳简介：曹阳教授先后在清华大学获得理学学士，硕士及博士（数学）等学位，然后在加州大学圣巴巴拉分校获得博士学位（计算机）。目前为弗吉尼亚理工大学（Virginia Tech)计算机系副教授。并先后在牛津大学数学中心，加州大学尔湾分校数学系及田纳西大学生物数学中心短期担任访问教授。

曹阳教授从事的研究方向为常微分方程数值解，生物系统模拟，随机系统的模拟等。目前主要致力于生物建模的方向。他在生物系统的建模方法，以及相应的随机模拟算法作出一些贡献，先后在国际期刊发表期刊论文五十多篇，获得两千多次引用。并且先后承担了六项美国国家自然科学基金项目的主要负责人，以及三项美国国家健康中心研究项目的主要参与人。2017年担任国际系统生物学年会的组委会主席。