Timothy L. Downing, Biophysical Regulation of Cell Fate, from ECM to Nuclear Chromatin

B378 Seminar room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Korea, Republic of

Abstract: The Downing lab investigates the intricate biophysical interactions between cells and their environment, elucidating their role in modulating adult cell behavior and phenotypic transitions via epigenetic regulation of gene expression. Leveraging diverse genome-scale sequencing techniques, we decipher mechanisms underlying cell fate transitions mediated through dynamic regulation of nuclear chromatin and heterogeneous gene activity. Our

Hyungsuk Tak, Statistical Challenges in Astronomical Time Delay Estimation (Cancelled)

B232 Seminar Room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Daejeon, Korea, Republic of

I present time delay estimation problems in astronomy as a part of time delay cosmography to infer the Hubble constant, the current expansion rate of the Universe. Time delay cosmography is based on strong gravitational lensing, an effect that multiple images of the same astronomical object appear in the sky because paths of the light

Summer Intern workshop 2024

  Presentor(s) Mentor Talk title Jaehun Jeong Gyuyoung Hwang Analyzing coupled SCN cell frequencies of mammals for multi-step transcriptional model Hyunsuk Choo, Yonghee Lee Seok Joo Chae Development of a data-driven causality detection method using Taken's Theorem Juhyeon Kim Dongju Lim Accurate initial condition for circadian pacemaker model estimating the circadian phase Kyeongtae Ko Dongju

Hyukpyo Hong, Koopman representation: Linear representation – not an approximation – of nonlinear dynamics

Abstract: A system of ordinary differential equations (ODEs) is one of the most widely used tools to describe a deterministic dynamical system. In general, such ODEs involve nonlinear equations, which make analysis of dynamical systems difficult. In this talk, we introduce Koopman theory, which offers a linear representation – not an approximation – of nonlinear dynamics. In particular, we present a data-driven algorithm to find such a linear representation

Uncovering personalized glucose responses and circadian rhythms from multiple wearable biosensors with Bayesian dynamical modeling

ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium) (pw: 1234)

Abstract: Wearable biosensors measure physiological variables with high temporal resolution over multiple days and are increasingly employed in clinical settings, such as continuous glucose monitoring in diabetes care. Such datasets bring new opportunities and challenges, and patients, clinicians, and researchers are today faced with a common challenge: how to best summarize and capture relevant information

Theoretical studies on biological oscillations by using waveform data and mathematical models – Shingo Gibo

Title: Theoretical studies on biological oscillations by using waveform data and mathematical models Abstract: Temporal waveforms of biological oscillations are of various shapes. In our research, we have explored the functional implications of these waveform shapes. In particular, we theoretically showed that the period of circadian clocks is proportional to the waveform distortion from sinusoidal wave. It suggests that the circadian period can be stable against temperature changes only if the waveform becomes more distorted at higher temperatures. In this talk, I will explain my past research and discuss my future plans. Reference: Shingo Gibo, Gen Kurosawa, Non-sinusoidal Waveform in Temperature Compensated Circadian Oscillations, Biophysical Journal 116 (4) 741-751 (2019). doi: 10.1016/j.bpj.2018.12.022 Shingo Gibo, Gen Kurosawa, Theoretical study on the regulation of circadian rhythms by RNA methylation, Journal of Theoretical Biology 490, 110140 (2020). doi; 10.1016/j.jtbi.2019.110140 Shingo Gibo, Teiji Kunihiro, Tetsuo Hatsuda, Gen Kurosawa, Waveform

Solving Inverse Problems in Medical Imaging with Score-Based Generative Models – U Jin Choi

B232 Seminar Room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Daejeon, Korea, Republic of

In this talk, we discuss the paper : “Solving Inverse Problems in Medical Imaging with Score-Based Generative Models” by Y Song et al. Reconstructing medical images from partial measurements is an important inverse problem in Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). Existing solutions based on machine learning typically train a model to directly

Diffusion Posterior Sampling for Linear Inverse Problem Solving- A Filtering Perspective – U Jin Choi

B232 Seminar Room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Daejeon, Korea, Republic of

In this talk, we discuss the paper : “Diffusion Posterior Sampling for Linear Inverse Problem Solving- A Filtering Perspective” by Z. Dou& Y. Song Diffusion models have achieved tremendous success in generating high-dimensional data like images, videos and audio. These models provide powerful data priors that can solve linear inverse problems in zero shot through

Enhanced Gaussian Process Surrogates for Optimization and Sampling by Pure Exploration – Hwanwoo Kim

B232 Seminar Room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Daejeon, Korea, Republic of

Abstract: In this talk, we propose novel noise-free Bayesian optimization strategies that rely on a random exploration step to enhance the accuracy of Gaussian process surrogate models. The new algorithms retain the ease of implementation of the classical GP-UCB algorithm, but the additional random exploration step accelerates their convergence, nearly achieving the optimal convergence rate.

Biomolecular Condensates: Principles and Models, Jeong-Mo Choi

B232 Seminar Room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Daejeon, Korea, Republic of

Over the past decade, the phase behavior of biomolecules has garnered significant attention, particularly due to its biological implications, such as the reversible formation and dissociation of biomolecular condensates. These condensates perform diverse and essential functions within cells, including the acceleration of chemical reactions. Recent advances aim to uncover the fundamental principles of these systems

IBS 의생명수학그룹 Biomedical Mathematics Group
기초과학연구원 수리및계산과학연구단 의생명수학그룹
대전 유성구 엑스포로 55 (우) 34126
IBS Biomedical Mathematics Group (BIMAG)
Institute for Basic Science (IBS)
55 Expo-ro Yuseong-gu Daejeon 34126 South Korea
Copyright © IBS 2021. All rights reserved.