BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Biomedical Mathematics Group - ECPv6.15.20//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://www.ibs.re.kr/bimag
X-WR-CALDESC:Events for Biomedical Mathematics Group
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Asia/Seoul
BEGIN:STANDARD
TZOFFSETFROM:+0900
TZOFFSETTO:+0900
TZNAME:KST
DTSTART:20250101T000000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20260102T100000
DTEND;TZID=Asia/Seoul:20260102T113000
DTSTAMP:20260422T140642
CREATED:20251231T002614Z
LAST-MODIFIED:20251231T002614Z
UID:12076-1767348000-1767353400@www.ibs.re.kr
SUMMARY:Seasonal timing and interindividual differences in shiftwork adaptation - Kang Min Lee
DESCRIPTION:In this talk\, we discuss the paper “Seasonal timing and interindividual differences in shiftwork adaptation” by R. Kim et al.\, npj digital medicine\, 2025. \nAbstract  \nMillions of shift workers in the U.S. face an increased risk of depression\, cancer\, and metabolic disease\, yet individual responses to shift work vary widely. We find that a conserved biological system of morning and evening oscillators\, which evolved for seasonal timing\, may contribute to these interindividual differences. In this study\, we analyze seasonality in medical interns working shifts\, revealing that summer-winter variation correlates with increased circadian misalignment after shift work. Mathematical modeling suggests that seasonal timing influences the rate of adaptation to new schedules\, predicting differential effects on morning and evening oscillators. Additionally\, we examine genetic polymorphisms linked to seasonality in animals and find that human variants can impact how quickly circadian rhythms respond to schedule changes. Based on our findings\, we hypothesize that the vast interindividual differences in shift work adaptation—critical for shift worker health—can in part be explained by biological mechanisms for seasonal timing.
URL:https://www.ibs.re.kr/bimag/event/seasonal-timing-and-interindividual-differences-in-shiftwork-adaptation-kang-min-lee/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20260109T100000
DTEND;TZID=Asia/Seoul:20260109T113000
DTSTAMP:20260422T140642
CREATED:20251231T002857Z
LAST-MODIFIED:20251231T002857Z
UID:12078-1767952800-1767958200@www.ibs.re.kr
SUMMARY:scPPDM: A Diffusion Model for Single-Cell Drug-Response Prediction - Aqsa Awan
DESCRIPTION:In this talk\, we discuss the paper “scPPDM: A Diffusion Model for Single-Cell Drug-Response Prediction” by Z. Liang et al.\, arxiv\, 2025. \nAbstract \nThis paper introduces the Single-Cell Perturbation Prediction Diffusion Model (scPPDM)\, the first diffusion-based framework for single-cell drug-response prediction from scRNA-seq data. scPPDM couples two condition channels\, pre-perturbation state and drug with dose\, in a unified latent space via non-concatenative GD-Attn. During inference\, factorized classifier-free guidance exposes two interpretable controls for state preservation and drug-response strength and maps dose to guidance magnitude for tunable intensity. Evaluated on the Tahoe-100M benchmark under two stringent regimes\, unseen covariate combinations (UC) and unseen drugs (UD)\, scPPDM sets new state-of-the-art results across log fold-change recovery\, delta correlations\, explained variance\, and DE-overlap. Representative gains include +36.11%/+34.21% on DEG logFC-Spearman/Pearson in UD over the second-best model. This control interface enables transparent what-if analyses and dose tuning\, reducing experimental burden while preserving biological specificity.
URL:https://www.ibs.re.kr/bimag/event/scppdm-a-diffusion-model-for-single-cell-drug-response-prediction-aqsa-awan/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20260115T100000
DTEND;TZID=Asia/Seoul:20260115T113000
DTSTAMP:20260422T140642
CREATED:20260109T124602Z
LAST-MODIFIED:20260109T124602Z
UID:12099-1768471200-1768476600@www.ibs.re.kr
SUMMARY:Quantifying interventional causality by knockoff operation - Olive Cawiding
DESCRIPTION:In this talk\, we discuss the paper\, “Quantifying interventional causality by knockoff operation” by Xinyan Zhang and Luonan Chen\, Science Advances\, 2025. \nAbstract  \nCausal inference between measured variables is crucial to understand the underlying mechanism of complex biological processes at a network level but remains challenging in computational biology. We propose an innovative causal criterion\, knockoff conditional mutual information (KOCMI)\, to accurately infer interventional direct causality without prior knowledge of the network structure using either time-independent or time-series data. KOCMI performs knockoff operation on a variable as its virtual intervention\, which preserves the original network structure\, and then identifies the causality between two variables by estimating the distributional invariance before and after such a virtual intervention. We show that\, algorithmically\, KOCMI enables quantification of causal relationship\, even for networks with loops\, and\, theoretically\, is also consistent with the do-calculus causal analyses but without their prerequisite of the network structure. KOCMI shows superior performance on benchmark and real datasets\, comparing with existing methods. Overall\, KOCMI provides a powerful tool in inferring interventional causality\, which is theoretically ensured and experimentally validated by real intervention data.
URL:https://www.ibs.re.kr/bimag/event/quantifying-interventional-causality-by-knockoff-operation-olive-cawiding/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20260123T100000
DTEND;TZID=Asia/Seoul:20260123T120000
DTSTAMP:20260422T140642
CREATED:20260116T013712Z
LAST-MODIFIED:20260119T002842Z
UID:12136-1769162400-1769169600@www.ibs.re.kr
SUMMARY:A wearable-based aging clock associates with disease and behavior - Myna Lim
DESCRIPTION:In this talk\, we discuss the paper\, “A wearable-based aging clock associates with disease and behavior” by A. C. Miller et al.\, Nature Comm\, 2025. \nAbstract  \nAging biomarkers play a vital role in understanding longevity\, with the potential to improve clinical decisions and interventions. Existing aging clocks typically use blood\, vitals\, or imaging collected in a clinical setting. Wearables\, in contrast\, can make frequent and inexpensive measurements throughout daily living. Here we develop PpgAge\, an aging clock using photoplethysmography at the wrist from a consumer wearable. Using the Apple Heart & Movement Study (n = 213\,593 participants; >149 million participant-days)\, our observational analysis shows that this non-invasive and passively collected aging clock accurately predicts chronological age and captures signs of healthy aging. Participants with an elevated PpgAge gap (i.e.\, predicted age greater than chronological age) have significantly higher diagnosis rates of heart disease\, heart failure\, and diabetes. Elevated PpgAge gap is also a significant predictor of incident heart disease events (and new diagnoses) when controlling for relevant risk factors. PpgAge also associates with behavior\, including smoking\, exercise\, and sleep. Longitudinally\, PpgAge exhibits a sharp increase during pregnancy and concurrent with certain types of cardiac events.
URL:https://www.ibs.re.kr/bimag/event/mapping-the-genetic-landscape-across-14-psychiatric-disorders-myna-lim/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20260130T100000
DTEND;TZID=Asia/Seoul:20260130T120000
DTSTAMP:20260422T140642
CREATED:20260116T013852Z
LAST-MODIFIED:20260116T013852Z
UID:12138-1769767200-1769774400@www.ibs.re.kr
SUMMARY:Generic Temperature Response of Large Biochemical Networks - Shingo Gibo
DESCRIPTION:In this talk\, we discuss the paper “Generic Temperature Response of Large Biochemical Networks” by Julian B. Voits and Ulrich S. Schwarz\, PRX Life\, 2025. \nAbstract  \nBiological systems are remarkably susceptible to relatively small temperature changes. The most obvious example is fever\, when a modest rise in body temperature of only few Kelvin has strong effects on our immune system and how it fights pathogens. Another very important example is climate change\, when even smaller temperature changes lead to dramatic shifts in ecosystems. Although it is generally accepted that the main effect of an increase in temperature is the acceleration of biochemical reactions according to the Arrhenius equation\, it is not clear how it affects large biochemical networks with complicated architectures. For developmental systems such as fly and frog\, it has been shown that the system response to temperature deviates in a characteristic manner from the linear Arrhenius plot of single reactions\, but a rigorous explanation has not been given yet. Here we use a graph-theoretical interpretation of the mean first-passage times of a biochemical master equation to give a statistical description. We find that in the limit of large system size and if the network has a bias towards a target state\, then the Arrhenius plot is generically quadratic\, in excellent agreement with numerical simulations for large networks as well as with experimental data for developmental times in fly. We also discuss under which conditions this generic response can be violated\, for example for linear chains\, which have only one spanning tree.
URL:https://www.ibs.re.kr/bimag/event/generic-temperature-response-of-large-biochemical-networks-shingo-gibo/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
END:VCALENDAR