기초과학연구원 의생명수학그룹
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 …
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 …
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 …
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 …
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 …
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 …
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 …
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 …
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 …
Abstract: TBA
Abstract: The biological master clock, the suprachiasmatic nucleus (SCN) of a mouse, contains many (~20,000) clock cells heterogeneous, particularly with respect to their circadian period. Despite the inhomogeneity, within an …
Abstract: We consider the problem of nonparametric imputation using neural network models. Neural network models can capture complex nonlinear trends and interaction effects, making it a powerful tool for predicting …
