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【学术报告】2021年5月20、21、22日贾晨教授举办学术讲座

时间:2021-05-19

报告人: 贾晨(北京计算科学研究中心)

邀请人:吴付科

(一)

报告时间:2021年5月20日(星期四)上午10:30-12:00

报告地点:科技楼(南楼)715室

报告题目:Single-cell stochastic gene expression dynamics along a cell lineage

报告摘要:The stochasticity of gene expression is manifested in the fluctuations of mRNA and protein copy numbers within a cell lineage over time. While data of this type can be obtained for many generations, most mathematical models are unsuitable to interpret such data since they assume non-growing cells. Here we develop a theoretical approach that quantitatively links the frequency content of lineage data to subcellular dynamics. We elucidate how the position, height, and width of the peaks in the power spectrum provide a distinctive fingerprint that encodes a wealth of information about mechanisms controlling transcription, translation, replication, degradation, bursting, promoter switching, cell cycle duration, cell division, gene dosage compensation, and cell size homeostasis. Predictions are confirmed by analysis of single-cell Escherichia coli data obtained using fluorescence microscopy. Furthermore, by matching the experimental and theoretical power spectra, we infer the temperature-dependent gene expression parameters, without the need of measurements relating fluorescence intensities to molecule numbers.

(二)

报告时间:2021年5月21日(星期五)上午10:00-11:30

报告地点:科技楼(南楼)702室

报告题目:Cell size distribution of lineage data: analytic results and parameter inference

报告摘要:Recent advances in single-cell technologies have enabled time-resolved measurements of the cell size over several cell cycles. This data encodes information on how cells correct size aberrations so that they do not grow abnormally large or small. Here we formulate a piecewise deterministic Markov model describing the evolution of the cell size over many generations, for all three cell size homeostasis strategies (timer, sizer, and adder). The model is solved to obtain an analytical expression for the non-Gaussian cell size distribution in a cell lineage; the theory is used to understand how the shape of the distribution is influenced by the parameters controlling the dynamics of the cell cycle and by the choice of cell tracking protocol. The theoretical cell size distribution is found to provide an excellent match to the experimental cell size distribution of E. coli lineage data collected under various growth conditions.

(三)

报告时间:2021年5月22日(星期六)上午9:30-11:00

报告地点:科技楼(南楼)611室

报告题目:单细胞随机基因表达动力学的数学理论简介

报告摘要:许多重要的细胞过程都基于基因调控,因此揭示基因表达机制对于理解基本的细胞内部过程是极端重要的。然而,由于基因表达是一个复杂的生化过程,对其建立合理的生物数学模型,并由此解释最新的实验现象是一项极具挑战性的任务,相关研究目前仍然是计算系统生物学的研究热点与前沿。我将结合我与合作者的最新研究成果,简要介绍基因表达系统的数学建模与分析方法,希望能起到抛砖引玉的作用。





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