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PRODID:-//Biomedical Mathematics Group - ECPv6.16.2//NONSGML v1.0//EN
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X-ORIGINAL-URL:https://www.ibs.re.kr/bimag
X-WR-CALDESC:Events for Biomedical Mathematics Group
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X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Asia/Seoul
BEGIN:STANDARD
TZOFFSETFROM:+0900
TZOFFSETTO:+0900
TZNAME:KST
DTSTART:20230101T000000
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END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20240712T140000
DTEND;TZID=Asia/Seoul:20240712T160000
DTSTAMP:20260522T084038
CREATED:20240624T002744Z
LAST-MODIFIED:20240709T021017Z
UID:9734-1720792800-1720800000@www.ibs.re.kr
SUMMARY:Seokjoo Chae\, Holimap: an accurate and efficient method for solving stochastic gene network dynamics
DESCRIPTION:In this talk\, we discuss the paper “Holimap: an accurate and efficient method for solving stochastic gene network dynamics” by Chen Jia and Ramon Grima\, bioRxiv\, 2024. \nAbstract  \nGene-gene interactions are crucial to the control of sub-cellular processes but our understanding of their stochastic dynamics is hindered by the lack of simulation methods that can accurately and efficiently predict how the distributions of protein numbers for each gene vary across parameter space. To overcome these difficulties\, here we present Holimap (high-order linear-mapping approximation)\, an approach that approximates the protein number distributions of a complex gene network by the distributions of a much simpler reaction system. We demonstrate Holimap’s computational advantages over conventional methods by applying it to predict the stochastic time-dependent protein dynamics of several gene regulatory networks\, ranging from simple autoregulatory loops to complex randomly connected networks. Holimap is ideally suited to study how the intricate network of gene-gene interactions results in precise coordination and control of gene expression.
URL:https://www.ibs.re.kr/bimag/event/seokjoo-chae-feedback-between-stochastic-gene-networks-and-population-dynamics-enables-cellular-decision-making/
LOCATION:Daejeon
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20240719T140000
DTEND;TZID=Asia/Seoul:20240719T160000
DTSTAMP:20260522T084038
CREATED:20240624T003304Z
LAST-MODIFIED:20240715T001749Z
UID:9738-1721397600-1721404800@www.ibs.re.kr
SUMMARY:Dongju Lim\, Stochastic representations of ion channel kinetics and exact stochastic simulation of neuronal dynamics.
DESCRIPTION:In this talk\, we discuss the paper “Stochastic representations of ion channel kinetics and exact stochastic simulation of neuronal dynamics” by D. F. Anderson\, B. Ermentrout and P. J. Thomas\, Journal of Computational Neuroscience\, 2015. \nAbstract \nIn this paper we provide two representations for stochastic ion channel kinetics\, and compare the perfor- mance of exact simulation with a commonly used numer- ical approximation strategy. The first representation we present is a random time change representation\, popular- ized by Thomas Kurtz\, with the second being analogous to a “Gillespie” representation. Exact stochastic algorithms are provided for the different representations\, which are prefer- able to either (a) fixed time step or (b) piecewise constant propensity algorithms\, which still appear in the literature. As examples\, we provide versions of the exact algorithms for the Morris-Lecar conductance based model\, and detail the error induced\, both in a weak and a strong sense\, by the use of approximate algorithms on this model. We include ready-to-use implementations of the random time change algorithm in both XPP and Matlab. Finally\, through the consideration of parametric sensitivity analysis\, we show how the representations presented here are useful in the development of further computational methods. The gen- eral representations and simulation strategies provided here are known in other parts of the sciences\, but less so in the present setting.
URL:https://www.ibs.re.kr/bimag/event/dongju-lim-feedback-between-stochastic-gene-networks-and-population-dynamics-enables-cellular-decision-making/
LOCATION:Daejeon
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20240726T140000
DTEND;TZID=Asia/Seoul:20240726T160000
DTSTAMP:20260522T084038
CREATED:20240624T003604Z
LAST-MODIFIED:20240709T021120Z
UID:9740-1722002400-1722009600@www.ibs.re.kr
SUMMARY:Eui Min Jeong\, Temperature compensation through kinetic regulation in biochemical oscillators.
DESCRIPTION:In this talk\, we discuss the paper “Temperature compensation through kinetic regulation in biochemical oscillators” by HaochenFu\, Chenyi Fei\, Qi Ouyang\, and Yuhai Tu\, to appear in PNAS.  \nAbstract  \nAlthough individual kinetic rates in biochemical reactions are sensitive to temperature\, most circadian clocks exhibit a relatively constant period across a wide range of temperatures\, a phenomenon called temperature compensation (TC). However\, it remains unclear how different biochemical oscillators achieve TC. In this study\, using representative biochemical oscillator models with different underlying reaction networks\, we demonstrate a general kinetic regulation mechanism for TC regardless of the network structure. We find that by driving the system into a regime far from onset where the period increases strongly with at least one of the kinetic rates in the system to balance its inverse dependence on other rates\, robust TC can be achieved for a wide range of parameters in different networks. 
URL:https://www.ibs.re.kr/bimag/event/eui-min-jeong-temperature-compensation-through-kinetic-regulation-in-biochemical-oscillators/
LOCATION:Daejeon
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20240731T103000
DTEND;TZID=Asia/Seoul:20240731T120000
DTSTAMP:20260522T084038
CREATED:20240730T102340Z
LAST-MODIFIED:20260404T011149Z
UID:9908-1722421800-1722427200@www.ibs.re.kr
SUMMARY:IBS BIMAG 2024 Summer Internship workshop
DESCRIPTION:  \n\n\n\nPresentor(s)\nMentor\nTalk title\n\n\nJaehun Jeong\nGyuyoung Hwang\nAnalyzing coupled SCN cell frequencies of mammals for multi-step transcriptional model\n\n\nHyunsuk Choo\, Yonghee Lee\nSeok Joo Chae\nDevelopment of a data-driven causality detection method using Taken’s Theorem\n\n\nJuhyeon Kim\nDongju Lim\nAccurate initial condition for circadian pacemaker model estimating the circadian phase\n\n\nKyeongtae Ko\nDongju Lim\nAccurate initial condition estimation of exposed individuals in SEIR model\n\n\nAshley L Lawas\nOlive R Cawiding\nAdvancing causal inference in complex systems through ODE-based methods\n\n\nSieun Lee\nOlive R Cawiding\nImproving efficiency of sleep disorder diagnosis via SymScore\n\n\nDaniel Shin\, Anar Rzayev\nOlive R Cawiding\nImproving Sleep Disorder Diagnosis Questionnaire (SLEEPS) by integrating Lifestyle Factors into Machine-learning algorithms\n\n\nShubhangi Kumar\nPan Li\nModelling cardiac pacemaking dysfunction in heart failure progression\n\n\nYejin Lee\nPan Li\nModelling beta-adrenergic regulation of calcium dynamics in human ventricular myocytes\n\n\nHyungu Lee\nYun Min Song\nPSG sleep pattern prediction from actigraphy data\n\n\nYujin Park\nYun Min Song\nValidating the usefulness of anchor sleep from sleep-wake patterns using ESS\n\n\nYoon Kim\nYun Min Song\nPredicting sleep onset latency\n\n\n\n 
URL:https://www.ibs.re.kr/bimag/event/summer-intern-workshop-2024/
LOCATION:Daejeon
CATEGORIES:Lunch Lab Meeting Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20240731T160000
DTEND;TZID=Asia/Seoul:20240731T170000
DTSTAMP:20260522T084038
CREATED:20240728T141528Z
LAST-MODIFIED:20240728T141528Z
UID:9889-1722441600-1722445200@www.ibs.re.kr
SUMMARY:Hyukpyo Hong\, Koopman representation: Linear representation – not an approximation – of nonlinear dynamics
DESCRIPTION: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
URL:https://www.ibs.re.kr/bimag/event/hyukpyo-hong-koopman-representation-linear-representation-not-an-approximation-of-nonlinear-dynamics/
LOCATION:Daejeon
CATEGORIES:Biomedical Mathematics Seminar
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
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