기초과학연구원 의생명수학그룹
This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234) Abstract: Millions of individuals track their steps, heart rate, and other physiological signals through wearables. This data …
We will discuss about "A stochastic oscillator model simulates the entrainment of vertebrate cellular clocks by light", Kumpost et al., bioRxiv (2021) The circadian clock is a cellular mechanism that …
We will discuss about "Highly accurate fluorogenic DNA sequencing with information theory–based error correction", Chen et al., Nature Biotechnology (2017) Eliminating errors in next-generation DNA sequencing has proved challenging. Here …
This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234) Abstract: Life science has been a prosperous subject for a long time, and is still developing with …
Abstract: TBA
Abstract: TBA
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 …
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 …
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 …
