기초과학연구원 의생명수학그룹
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 …
This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234) Facebook live streaming: https://www.facebook.com/10226475900150025/videos/10226475902790091 Age brings the benefit of experience and looking back at my job as a professor, there are a couple of things that fall into the category “I wish someone had told me that earlier”. In this seminar, I …
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 …
Oscillatory signals are ubiquitously observed in many different intracellular systems such as immune systems and DNA repair processes. While we know how oscillatory signals are created, we do not fully understand what a critical role they play to regulate signal pathway systems in cells. Recently by using a stochastic nucleosome system, we found that a …
In this talk, the speaker will present introductory materials about Bayesian Machine Learning. Abstract The problem of approximating the posterior distribution (or density estimation in general) is a crucial problem in Bayesian statistics, in which intractable integrals often become the computational bottleneck. MCMC sampling is the most widely used family of algorithms for approximating posteriors. …
We will discuss about "Extending Transfer Entropy Improves Identification of Effective Connectivity in a Spiking Cortical Network Model", Ito et. al., PloS ONE, 2011 Transfer entropy (TE) is an information-theoretic measure which has received recent attention in neuroscience for its potential to identify effective connectivity between neurons. Calculating TE for large ensembles of spiking neurons is …
We will discuss about "Independent Markov Decomposition: Towards modeling kinetics of biomolecular complexes", Hempel et. al., bioRxiv, 2021 In order to advance the mission of in silico cell biology, modeling the interactions of large and complex biological systems becomes increasingly relevant. The combination of molecular dynamics (MD) and Markov state models (MSMs) have enabled the construction of …
This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234) Abstract: Non-Markov models of stochastic biochemical kinetics often incorporate explicit time delays to effectively model large numbers of intermediate biochemical processes. Analysis and simulation of these models, as well as the inference of their parameters from data, are fraught with difficulties because …
This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234) Abstract: Accurate assessment of circadian timing is critical to many applications, including timing of drug delivery, prediction of neurobehavioral performance, and optimized scheduling of sleep. Current methods for measuring circadian timing are onerous and do not produce results in real time. Mathematical …
We will discuss about "DNA as a universal substrate for chemical kinetics ", Soloveichik et al., PNAS (2009) Molecular programming aims to systematically engineer molecular and chemical systems of autonomous function and ever-increasing complexity. A key goal is to develop embedded control circuitry within a chemical system to direct molecular events. Here we show that …
Abstract: TBA