We will discuss about "Synthetic multistability in mammalian cells", Zhu et al., bioRxiv (2021) In multicellular organisms, gene regulatory circuits generate thousands of molecularly distinct, mitotically heritable states, through the property of multistability. Designing synthetic multistable circuits would provide insight into natural cell fate control circuit architectures and allow engineering of multicellular programs that require …

We will discuss about "A Simple and Flexible Computational Framework for Inferring Sources of Heterogeneity from Single-Cell Dynamics", Dharmarajan et al., Cell Systems (2019) Single-cell time-lapse data provide the means for disentangling sources of cell-to-cell and intra-cellular variability, a key step for understanding heterogeneity in cell populations. However, single-cell analysis with dynamic models is a …

In this talk, the speaker will present introductory materials about Bayesian Machine Learning. Abstract Gaussian process(GP) is a stochastic process such that the joint distribution of an arbitrary finite subset of the random variables is a multivariate normal. It plays a fundamental role in Bayesian machine learning as it can be interpreted as a prior …