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PRODID:-//Biomedical Mathematics Group - ECPv6.17.2//NONSGML v1.0//EN
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METHOD:PUBLISH
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:20250101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20260703T100000
DTEND;TZID=Asia/Seoul:20260703T120000
DTSTAMP:20260528T012333Z
CREATED:20260527T140141Z
LAST-MODIFIED:20260528T012333Z
UID:12539-1783072800-1783080000@www.ibs.re.kr
SUMMARY:A Metabolism-Informed Neural Network Identifies Pathways Influencing the Potency and Toxicity of Antimicrobial Combinations - Se Jun Ahn
DESCRIPTION:In this talk\, we discuss the paper “A Metabolism-Informed Neural Network Identifies Pathways Influencing the Potency and Toxicity of Antimicrobial Combinations” by Harkirat Sigh Arora et al.\, npj drug discovery\, 2026. \nAbstract: \nAntimicrobial resistance poses a major global threat\, driven by diminishing efficacy of current treatments and limited new therapies. Combination therapy with existing drugs offers a promising solution\, yet current empirical screening methods are expensive and often lead to suboptimal efficacy and inadvertent toxicity. We introduce CALMA\, a computational framework that quantitatively analyzes the potency-toxicity landscape of multi-drug combinations. Integrating genome-scale metabolic modeling with a neural network that reflects metabolic subsystems\, CALMA enhances interpretability and prioritizes pathways influencing drug interactions. The incorporation of metabolic architecture in the neural network leads to over 92% reduction in model parameters\, enabling it to learn generalizable mechanistic signals and reducing the experimental search space of optimal combinations by 97%. CALMA identified promising antimicrobial combinations against Escherichia coli and Mycobacterium tuberculosis that were antagonistic for kidney and liver toxicity and uncovered the nucleotide salvage pathway as a selective influencer of toxicity\, which was validated in vitro. Mining of health records of over 400\,000 patients showed reduced frequency of kidney side-effects in patients taking a vancomycin combination identified by CALMA. CALMA provides a rational\, mechanistic approach to streamline combination treatment design.
URL:https://www.ibs.re.kr/bimag/event/a-metabolism-informed-neural-network-identifies-pathways-influencing-the-potency-and-toxicity-of-antimicrobial-combinations-se-jun-ahn/
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:20260706T100000
DTEND;TZID=Asia/Seoul:20260706T110000
DTSTAMP:20260701T084146Z
CREATED:20260616T012906Z
LAST-MODIFIED:20260701T084146Z
UID:12611-1783332000-1783335600@www.ibs.re.kr
SUMMARY:The effect of the fitness gradient - Jakub Svoboda
DESCRIPTION:Abstract: \nEvolutionary biology studies populations of reproducing individuals and how their composition changes over time.An important question is the fixation probability of a single mutant that attempts to invade a homogeneous population.Many real populations experience gradients of chemicals or nutrients that cause mutations to be beneficial in some spatial regions and harmful in others.We will examine the fixation probability of a mutant placed on a simple one-dimensional spatial structure that experiences such a gradient.The mutant’s fitness varies linearly but is on average 1\, whereas the resident’s fitness is constant and equal to 1.We will prove nonintuitive results about the fixation probability of mutants.
URL:https://www.ibs.re.kr/bimag/event/the-effect-of-the-fitness-gradient-jakub-svoboda/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Biomedical Mathematics Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20260709T100000
DTEND;TZID=Asia/Seoul:20260709T110000
DTSTAMP:20260708T001039Z
CREATED:20260708T001039Z
LAST-MODIFIED:20260708T001039Z
UID:12695-1783591200-1783594800@www.ibs.re.kr
SUMMARY:Advanced Iterative Methods as Elementary Iterations on Larger Spaces - Jongho Park
DESCRIPTION:Abstract: \nA central goal of scientific computing is to develop accurate and efficient solvers for scientific problems\, and this goal is often pursued through sophisticated numerical methods. In modern machine learning\, by contrast\, the basic optimization procedure is often comparatively simple\, typically gradient descent and its variants\, while much of the complexity is shifted to larger models. This talk examines this contrast from the viewpoint of scientific computing.We show that many advanced iterative methods\, including domain decomposition and multigrid methods\, can be interpreted as elementary iterations applied to equivalent problems posed on larger spaces. For example\, a classical multigrid method can be viewed as a Gauss–Seidel iteration for a suitable expanded system associated with a multilevel frame. To make this interpretation rigorous\, we introduce an auxiliary-space framework that recasts an iterative method for the original system as an equivalent\, but more elementary\, method for a lifted auxiliary system.The framework applies to a broad range of advanced methods. We illustrate its utility through applications to various modern iterative methods. Finally\, we discuss how this viewpoint can inform the design of numerical methods for problems arising in machine learning.
URL:https://www.ibs.re.kr/bimag/event/advanced-iterative-methods-as-elementary-iterations-on-larger-spaces-jongho-park/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Biomedical Mathematics Seminar
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20260710T100000
DTEND;TZID=Asia/Seoul:20260710T120000
DTSTAMP:20260629T080759Z
CREATED:20260629T080759Z
LAST-MODIFIED:20260629T080759Z
UID:12659-1783677600-1783684800@www.ibs.re.kr
SUMMARY:Topological identification and interpretation for single-cell gene regulation elucidation across multiple platforms using scMGCA - Yun Min Song
DESCRIPTION:In this talk\, we discuss the paper “Topological identification and interpretation for single-cell gene regulation elucidation across multiple platforms using scMGCA” by Zhuohan Yu et al.\, nature communications\, 2023. \nAbstract: \n\n\n\nSingle-cell RNA sequencing provides high-throughput gene expression information to explore cellular heterogeneity at the individual cell level. A major challenge in characterizing high-throughput gene expression data arises from challenges related to dimensionality\, and the prevalence of dropout events. To address these concerns\, we develop a deep graph learning method\, scMGCA\, for single-cell data analysis. scMGCA is based on a graph-embedding autoencoder that simultaneously learns cell-cell topology representation and cluster assignments. We show that scMGCA is accurate and effective for cell segregation and batch effect correction\, outperforming other state-of-the-art models across multiple platforms. In addition\, we perform genomic interpretation on the key compressed transcriptomic space of the graph-embedding autoencoder to demonstrate the underlying gene regulation mechanism. We demonstrate that in a pancreatic ductal adenocarcinoma dataset\, scMGCA successfully provides annotations on the specific cell types and reveals differential gene expression levels across multiple tumor-associated and cell signalling pathways.
URL:https://www.ibs.re.kr/bimag/event/topological-identification-and-interpretation-for-single-cell-gene-regulation-elucidation-across-multiple-platforms-using-scmgca-yun-min-song/
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:20260724T100000
DTEND;TZID=Asia/Seoul:20260724T120000
DTSTAMP:20260713T062127Z
CREATED:20260713T062127Z
LAST-MODIFIED:20260713T062127Z
UID:12700-1784887200-1784894400@www.ibs.re.kr
SUMMARY:Topology identifies concurrent cyclic processes in single-cell transcriptomics and androgen receptor function - Seongjin Choi
DESCRIPTION:In this talk\, we discuss the paper “Topology identifies concurrent cyclic processes in single-cell transcriptomics and androgen receptor function” by Kelly Maggs et al.\, bioRxiv\, 2025. \nAbstract: \n\nStandard single-cell RNA-seq analysis frameworks aggregate over-lapping biological processes and impose a single parametrization\, conflating distinct programs. Here\, we introduce a topological framework that detects and disentangles multiple cyclic processes directly from single-cell transcriptomic data. We validate this approach on synthetic datasets and scRNA-seq profiles of human dermal fibroblasts under control conditions and following androgen receptor (AR) silencing\, as well as in vivo mouse prostate regeneration under androgen receptor add-back. We show robust cell cycle structure across conditions\, identify an unbiased AR-linked stress signature related to the senescence and proliferation across organisms\, and uncover cholesterol homeostasis as an AR-linked program in tissue regeneration. This framework enables identification and separation of concurrent cyclic processes from snapshot single-cell data\, revealing complex multi-dimensional regulatory dynamics inaccessible to standard clustering analysis.
URL:https://www.ibs.re.kr/bimag/event/topology-identifies-concurrent-cyclic-processes-in-single-cell-transcriptomics-and-androgen-receptor-function-seongjin-choi/
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:20260728T160000
DTEND;TZID=Asia/Seoul:20260728T170000
DTSTAMP:20260713T132333Z
CREATED:20260713T061641Z
LAST-MODIFIED:20260713T132333Z
UID:12698-1785254400-1785258000@www.ibs.re.kr
SUMMARY:Global Linearization of Nonlinear Dynamics via Koopman Operators: A Gentle Introduction\, Applications\, and Open Challenges - Hyukpyo Hong
DESCRIPTION:Abstract: \nA central challenge of modern dynamical systems theory is to make nonlinear systems tractable without sacrificing fidelity. Koopman operator theory pursues this goal by lifting nonlinear dynamics into a linear\, but infinite dimensional\, operator acting on a function space. This operator-theoretic perspective underlies a broad class of modern data-driven methods\, from dynamic mode decomposition to equation discovery in scientific machine learning for fluid dynamics and neuroscience. Yet this power comes at a price: the operator’s infinite dimensionality poses a fundamental obstacle to computation and practical use\, and finding tractable finite-dimensional approximations remains an open and active challenge. In this talk\, I will first introduce the basic principles of Koopman operator theory and survey some of the results that have made it a cornerstone of modern dynamical systems analysis. I will then briefly describe two of my works on finite-dimensional Koopman representations. Finally\, I will turn to my recent work on non-autonomous dynamical system learning\, in collaboration with Prof. Dae Wook Kim.
URL:https://www.ibs.re.kr/bimag/event/global-linearization-of-nonlinear-dynamics-via-koopman-operators-a-gentle-introduction-applications-and-open-challenges-hyukpyo-hong/
LOCATION:108\, Conference Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Korea\, Republic of
CATEGORIES:Biomedical Mathematics Seminar
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20260731T100000
DTEND;TZID=Asia/Seoul:20260731T120000
DTSTAMP:20260730T020723Z
CREATED:20260629T081120Z
LAST-MODIFIED:20260730T020723Z
UID:12661-1785492000-1785499200@www.ibs.re.kr
SUMMARY:Fast training of accurate physics-informed neural networks without gradient descent - Seunghun Lee
DESCRIPTION:In this talk\, we discuss the paper “Fast training of accurate physics-informed neural networks without gradient descent” by Chinmay Datar et al.\, ICLR\, 2026. \nAbstract: \nSolving time-dependent Partial Differential Equations (PDEs) is one of the most critical problems in computational science. While Physics-Informed Neural Networks (PINNs) offer a promising framework for approximating PDE solutions\, their accuracy and training speed are limited by two core barriers: gradient-descent-based iterative optimization over complex loss landscapes and non-causal treatment of time as an extra spatial dimension. We present Frozen-PINN\, a novel PINN based on the principle of space-time separation that leverages random features instead of training with gradient descent\, and incorporates temporal causality by construction. On nine PDE benchmarks\, including challenges like extreme advection speeds\, shocks\, and high-dimensionality\, Frozen-PINNs achieve superior training efficiency and accuracy over state-of-the-art PINNs\, often by several orders of magnitude. Our work addresses longstanding training and accuracy bottlenecks of PINNs\, delivering quickly trainable\, highly accurate\, and inherently causal PDE solvers\, a combination that prior methods could not realize. Our approach challenges the reliance of PINNs on stochastic gradient-descent-based methods and specialized hardware\, leading to a paradigm shift in PINN training and providing a challenging benchmark for the community.
URL:https://www.ibs.re.kr/bimag/event/oscillatory-network-efficiency-predicts-mood-and-fatigue-during-sleep-deprivation-seunghun-lee/
LOCATION:108\, Conference Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
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