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Holimap: an accurate and efficient method for solving stochastic gene network dynamics

发布时间:2024-05-28 作者:77779193永利集团 浏览次数:
Speaker: 贾晨 DateTime: 2024年5月30日(周四)下午15:00-17:00
Brief Introduction to Speaker:

贾晨,北京计算科学研究中心特聘研究员,博士生导师,国家海外高层次青年人才。于北京大学数学科学学院取得学士学位与博士学位,博士毕业后赴美任助理研究员,随后回国并加入北京计算科学研究中心。贾晨主要从事数学、生物学、物理学等交叉领域的研究,特别是复杂生化网络的随机动力学与随机热力学研究。目前任中国运筹学会计算系统生物学分会青年理事,中国工业与应用数学学会数学生命科学专委会委员,中国生物信息学学会网络生物学专委会委员,中国生物信息学学会算法研究专委会委员。主持国家自然科学基金面上项目,参与国家自然科学基金重点项目。以第一作者或通讯作者发表学术论文近50篇,多项研究工作发表在PRX, Cell子刊, SIAM汇刊, PCB, JCP, AAP, EJP, JMB等相关领域内的权威杂志上。


Place: 6号楼M415会议室
Abstract:Gene-gene interactions are crucial to the control of sub-cellular processes but our understanding of their stochastic dynamics is hindered by the lack of simulation methods that can accurately and efficiently predict how the distributions of gene product numbers for each gene vary across parameter space. To overcome these difficulties, here we present Holimap (high-order linear-mapping approximation), an approach that approximates the protein or mRNA number distributions of a complex gene regulatory network by the distributions of a much simpler reaction system. We demonstrate Holimap's computational advantages over conventional methods by applying it to predict the stochastic time-dependent dynamics of various gene networks, including transcriptional networks ranging from simple autoregulatory loops to complex randomly connected networks, post-transcriptional networks, and post-translational networks. Holimap is ideally suited to study how the intricate network of gene-gene interac...