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X-WR-CALNAME:Biomedical Mathematics Group
X-ORIGINAL-URL:https://www.ibs.re.kr/bimag
X-WR-CALDESC:Events for Biomedical Mathematics Group
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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:20250530T140000
DTEND;TZID=Asia/Seoul:20250530T160000
DTSTAMP:20260422T145735
CREATED:20250426T143239Z
LAST-MODIFIED:20250528T035910Z
UID:11061-1748613600-1748620800@www.ibs.re.kr
SUMMARY:Direct Estimation of Parameters in ODE Models Using WENDy - Kangmin Lee
DESCRIPTION:In this talk\, we discuss the paper “Direct Estimation of Parameters in ODE Models Using WENDy: Weak-Form Estimation of Nonlinear Dynamics” by David M. Bortz\, Daniel A. Messenger\, and Vanja Dukic\, Bulletin of Mathematical Biology\, 2023. \nAbstract \nWe introduce the Weak-form Estimation of Nonlinear Dynamics (WENDy) method for estimating model parameters for non-linear systems of ODEs. Without relying on any numerical differential equation solvers\, WENDy computes accurate estimates and is robust to large (biologically relevant) levels of measurement noise. For low dimensional systems with modest amounts of data\, WENDy is competitive with conventional forward solver-based nonlinear least squares methods in terms of speed and accuracy. For both higher dimensional systems and stiff systems\, WENDy is typically both faster (often by orders of magnitude) and more accurate than forward solver-based approaches. The core mathematical idea involves an efficient conversion of the strong form representation of a model to its weak form\, and then solving a regression problem to perform parameter inference. The core statistical idea rests on the Errors-In-Variables framework\, which necessitates the use of the iteratively reweighted least squares algorithm. Further improvements are obtained by using orthonormal test functions\, created from a set of C∞ bump functions of varying support sizes.We demonstrate the high robustness and computational efficiency by applying WENDy to estimate parameters in some common models from population biology\, neuroscience\, and biochemistry\, including logistic growth\, Lotka-Volterra\, FitzHugh-Nagumo\, Hindmarsh-Rose\, and a Protein Transduction Benchmark model. Software and code for reproducing the examples is available at https://github.com/MathBioCU/WENDy.
URL:https://www.ibs.re.kr/bimag/event/quantifying-and-correcting-bias-in-transcriptional-parameter-inference-from-single-cell-data-kangmin-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:20250530T110000
DTEND;TZID=Asia/Seoul:20250530T120000
DTSTAMP:20260422T145735
CREATED:20250217T081212Z
LAST-MODIFIED:20250217T082031Z
UID:10780-1748602800-1748606400@www.ibs.re.kr
SUMMARY:Koopman operator approach to complex rhythmic systems - Hiroya Nakao
DESCRIPTION:Abstract \nSpontaneous rhythmic oscillations are widely observed in real-world systems. Synchronized rhythmic oscillations often provide important functions for biological or engineered systems. One of the useful theoretical methods for analyzing rhythmic oscillations is the phase reduction theory for weakly perturbed limit-cycle oscillators\, which systematically gives a low-dimensional description of the oscillatory dynamics using only the asymptotic phase of the oscillator. Recent advances in Koopman operator theory provide a new viewpoint on phase reduction\, yielding an operator-theoretic definition of the classical notion of the asymptotic phase and\, moreover\, of the amplitudes\, which characterize distances from the limit cycle. This led to the generalization of classical phase reduction to phase-amplitude reduction\, which can characterize amplitude deviations of the oscillator from the unperturbed limit cycle in addition to the phase along the cycle in a systematic manner. In the talk\, these theories are briefly reviewed and then applied to several examples of synchronizing rhythmic systems\, including biological oscillators\, networked dynamical systems\, and rhythmic spatiotemporal patterns.
URL:https://www.ibs.re.kr/bimag/event/koopman-operator-approach-to-complex-rhythmic-systems-hiroya-nakao/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2025/02/nakao-hiroya.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20250521T160000
DTEND;TZID=Asia/Seoul:20250521T170000
DTSTAMP:20260422T145735
CREATED:20250217T080703Z
LAST-MODIFIED:20250217T080703Z
UID:10775-1747843200-1747846800@www.ibs.re.kr
SUMMARY:Simplified descriptions of stochastic oscillators - Benjamin Lindner
DESCRIPTION:Abstract \nMany natural systems exhibit oscillations that show sizeable fluctuations in frequency and amplitude. This variability can arise from a wide variety of physical mechanisms. Phase descriptions that work for deterministic oscillators have a limited applicability for stochastic oscillators. In my talk I review attempts to generalize the phase concept to stochastic oscillations\, specifically\, the mean-return-time phase and the asymptotic phase.\nFor stochastic systems described by Fokker-Planck and Kolmogorov-backward equations\, I introduce a mapping of the system’s variables to a complex pointer (instead of a real-valued phase) that is based on the eigenfunction of the Kolmogorov equation. Under the new (complex-valued) description\, the statistics of the oscillator’s spontaneous activity\, of its response to external perturbations\, and of the coordinated activity of (weakly) coupled oscillators\, is brought into a universal and greatly simplified form. The theory is tested for three theoretical models of noisy oscillators arising from fundamentally different mechanisms: a damped harmonic oscillator with dynamical noise\, a fluctuation-perturbed limit-cycle system\, and an excitable system in which oscillations require noise to occur.
URL:https://www.ibs.re.kr/bimag/event/simplified-descriptions-of-stochastic-oscillators-benjamin-lindner/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2025/02/Benjamin-Lindner-e1739779616840.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20250509T140000
DTEND;TZID=Asia/Seoul:20250509T160000
DTSTAMP:20260422T145735
CREATED:20250426T142850Z
LAST-MODIFIED:20250507T002814Z
UID:11058-1746799200-1746806400@www.ibs.re.kr
SUMMARY:Network inference from short\, noisy\, low time-resolution\, partial measurements: Application to C. elegans neuronal calcium dynamics - Olive Cawiding
DESCRIPTION:In this talk\, we discuss the paper “Network inference from short\, noisy\, low time-resolution\, partial measurements: Application to C. elegans neuronal calcium dynamics” by Amitava Banerjee\, Sarthak Chandra\, and Edward Ott\, PNAS\, 2023. \nAbstract \nNetwork link inference from measured time series data of the behavior of dynamically interacting network nodes is an important problem with wide-ranging applications\, e.g.\, estimating synaptic connectivity among neurons from measurements of their calcium fluorescence. Network inference methods typically begin by using the measured time series to assign to any given ordered pair of nodes a numerical score reflecting the likelihood of a directed link between those two nodes. In typical cases\, the measured time series data may be subject to limitations\, including limited duration\, low sampling rate\, observational noise\, and partial nodal state measurement. However\, it is unknown how the performance of link inference techniques on such datasets depends on these experimental limitations of data acquisition. Here\, we utilize both synthetic data generated from coupled chaotic systems as well as experimental data obtained from Caenorhabditis elegans neural activity to systematically assess the influence of data limitations on the character of scores reflecting the likelihood of a directed link between a given node pair. We do this for three network inference techniques: Granger causality\, transfer entropy\, and\, a machine learning-based method. Furthermore\, we assess the ability of appropriate surrogate data to determine statistical confidence levels associated with the results of link-inference techniques.
URL:https://www.ibs.re.kr/bimag/event/chaos-is-not-rare-in-natural-ecosystems-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:20250502T140000
DTEND;TZID=Asia/Seoul:20250502T160000
DTSTAMP:20260422T145735
CREATED:20250330T073307Z
LAST-MODIFIED:20250424T070416Z
UID:10929-1746194400-1746201600@www.ibs.re.kr
SUMMARY:Boolean modelling as a logic-based dynamic approach in systems medicine - Kevin Spinicci
DESCRIPTION:In this talk\, we discuss the paper “Boolean modelling as a logic-based dynamic approach in systems medicine” by Ahmed Abdelmonem Hemedan et al.\, Computational and Structural biotechnology journal (2022). \nAbstract  \nMolecular mechanisms of health and disease are often represented as systems biology diagrams\, and the coverage of such representation constantly increases. These static diagrams can be transformed into dynamic models\, allowing for in silico simulations and predictions. Boolean modelling is an approach based on an abstract representation of the system. It emphasises the qualitative modelling of biological systems in which each biomolecule can take two possible values: zero for absent or inactive\, one for present or active. Because of this approximation\, Boolean modelling is applicable to large diagrams\, allowing to capture their dynamic properties. We review Boolean models of disease mechanisms and compare a range of methods and tools used for analysis processes. We explain the methodology of Boolean analysis focusing on its application in disease modelling. Finally\, we discuss its practical application in analysing signal transduction and gene regulatory pathways in health and disease.
URL:https://www.ibs.re.kr/bimag/event/boolean-modelling-as-a-logic-based-dynamic-approach-in-systems-medicine-kevin-spinicci/
LOCATION:Daejeon
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20250428T110000
DTEND;TZID=Asia/Seoul:20250428T120000
DTSTAMP:20260422T145735
CREATED:20250414T004912Z
LAST-MODIFIED:20250420T085852Z
UID:10975-1745838000-1745841600@www.ibs.re.kr
SUMMARY:FoodSeq: Using Genomics to Track and Study Diet - Lawrence David
DESCRIPTION:Abstract\nDietary assessment is crucial for understanding the relationship between diet and health. Yet traditional recall-based methods for tracking diet often face challenges like participant compliance and accurate recall. To address these issues\, our lab at Duke University has developed FoodSeq\, a genomic approach to track food intake through DNA sequencing of stool samples. In this talk\, I will explain how FoodSeq can identify and quantify dietary species\, allowing for objective and comprehensive monitoring of food consumption. We will explore the methodology behind FoodSeq\, including DNA extraction\, amplification\, and sequencing\, as well as data analysis. I will then present case studies demonstrating how FoodSeq can be used in clinical studies involving patients undergoing hematopoietic stem cell transplant\, highlighting the potential to contribute insights into nutrition\, health\, and the microbiome.
URL:https://www.ibs.re.kr/bimag/event/foodseq-using-genomics-to-track-and-study-diet-lawrence-david/
LOCATION:Conference room\, (B109)\, Daejeon\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Biomedical Mathematics Seminar
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2025/04/0604222-e1745139516483.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20250422T160000
DTEND;TZID=Asia/Seoul:20250422T170000
DTSTAMP:20260422T145735
CREATED:20250421T005522Z
LAST-MODIFIED:20250422T064931Z
UID:10994-1745337600-1745341200@www.ibs.re.kr
SUMMARY:Dimensionality Reduction and Summary-Statistical Modeling in Genetic Studies - Fatemeh Yavartanoo
DESCRIPTION:Abstract: \nThis presentation introduces DRLPC and a refined summary-statistics method to improve genetic association analysis. Applications to cognition\, neurodegenerative diseases\, and high cholesterol are discussed\, with future directions in single-cell analysis and drug target discovery.
URL:https://www.ibs.re.kr/bimag/event/tba-fatemeh-yavartanoo/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Biomedical Mathematics Seminar
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2025/04/1705897753193.jpeg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20250418T140000
DTEND;TZID=Asia/Seoul:20250418T160000
DTSTAMP:20260422T145735
CREATED:20250327T010619Z
LAST-MODIFIED:20250327T010619Z
UID:10923-1744984800-1744992000@www.ibs.re.kr
SUMMARY:Identifying key drivers in a stochastic dynamical system through estimation of transfer entropy between univariate and multivariate time series - Yun Min Song
DESCRIPTION:In this talk\, we discuss the paper “Identifying key drivers in a stochastic dynamical system through estimation of transfer entropy between univariate and multivariate time series” by Julian Lee\, Physical Review E\, 2025. \nAbstract  \nTransfer entropy (TE) is a widely used tool for quantifying causal relationships in stochastic dynamical systems. Traditionally\, TE and its conditional variants are applied pairwise between dynamic variables to infer these relationships. However\, identifying key drivers in such systems requires a measure of the causal influence exerted by each component on the entire system. I propose using outgoing transfer entropy (OutTE)\, the transfer entropy from a given variable to the collection of remaining variables\, to quantify the causal influence of the variable on the rest of the system. Conversely\, the incoming transfer entropy (InTE) is also defined to quantify the causal influence received by a component from the rest of the system. Since OutTE and InTE involve transfer entropy between univariate and multivariate time series\, naive estimation methods can result in significant errors\, especially when the number of variables is large relative to the number of samples. To address this\, I introduce a novel estimation scheme that computes outgoing and incoming TE only between significantly interacting partners. The feasibility and effectiveness of this approach are demonstrated using synthetic data and real oral microbiota data. The method successfully identifies the bacterial species known to be key players in the bacterial community\, highlighting its potential for uncovering causal drivers in complex systems.
URL:https://www.ibs.re.kr/bimag/event/identifying-key-drivers-in-a-stochastic-dynamical-system-through-estimation-of-transfer-entropy-between-univariate-and-multivariate-time-series-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:20250411T140000
DTEND;TZID=Asia/Seoul:20250411T160000
DTSTAMP:20260422T145735
CREATED:20250327T010416Z
LAST-MODIFIED:20250327T010416Z
UID:10921-1744380000-1744387200@www.ibs.re.kr
SUMMARY:Entrainment and multi-stability of the p53 oscillator in human cells - Eui Min Jeong
DESCRIPTION:In this talk\, we discuss the paper\, “Entrainment and multi-stability of the p53 oscillator in human cells” by Alba Jiménez et al.\, Cell Systems\, 2024. \nAbstract  \nThe tumor suppressor p53 responds to cellular stress and activates transcription programs critical for regulating cell fate. DNA damage triggers oscillations in p53 levels with a robust period. Guided by the theory of synchronization and entrainment\, we developed a mathematical model and experimental system to test the ability of the p53 oscillator to entrain to external drug pulses of various periods and strengths. We found that the p53 oscillator can be locked and entrained to a wide range of entrainment modes. External periods far from p53’s natural oscillations increased the heterogeneity between individual cells whereas stronger inputs reduced it. Single-cell measurements allowed deriving the phase response curves (PRCs) and multiple Arnold tongues of p53. In addition\, multi-stability and non-linear behaviors were mathematically predicted and experimentally detected\, including mode hopping\, period doubling\, and chaos. Our work revealed critical dynamical properties of the p53 oscillator and provided insights into understanding and controlling it. A record of this paper’s transparent peer review process is included in the supplemental information.
URL:https://www.ibs.re.kr/bimag/event/entrainment-and-multi-stability-of-the-p53-oscillator-in-human-cells-eui-min-jeong/
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:20250404T140000
DTEND;TZID=Asia/Seoul:20250404T160000
DTSTAMP:20260422T145735
CREATED:20250326T091007Z
LAST-MODIFIED:20250330T013324Z
UID:10919-1743775200-1743782400@www.ibs.re.kr
SUMMARY:Accurate predictions on small data with a tabular foundation model - Dongju Lim
DESCRIPTION:In this talk\, we discuss the paper “Accurate predictions on small data with a tabular foundation model” by Noah Hollmann et al.\, Nature (2025). \nAbstract \nTabular data\, spreadsheets organized in rows and columns\, are ubiquitous across scientific fields\, from biomedicine to particle physics to economics and climate science1\,2. The fundamental prediction task of filling in missing values of a label column based on the rest of the columns is essential for various applications as diverse as biomedical risk models\, drug discovery and materials science. Although deep learning has revolutionized learning from raw data and led to numerous high-profile success stories3\,4\,5\, gradient-boosted decision trees6\,7\,8\,9 have dominated tabular data for the past 20 years. Here we present the Tabular Prior-data Fitted Network (TabPFN)\, a tabular foundation model that outperforms all previous methods on datasets with up to 10\,000 samples by a wide margin\, using substantially less training time. In 2.8 s\, TabPFN outperforms an ensemble of the strongest baselines tuned for 4 h in a classification setting. As a generative transformer-based foundation model\, this model also allows fine-tuning\, data generation\, density estimation and learning reusable embeddings. TabPFN is a learning algorithm that is itself learned across millions of synthetic datasets\, demonstrating the power of this approach for algorithm development. By improving modelling abilities across diverse fields\, TabPFN has the potential to accelerate scientific discovery and enhance important decision-making in various domains.
URL:https://www.ibs.re.kr/bimag/event/a-differentiable-gillespie-algorithm-for-simulating-chemical-kinetics-parameter-estimation-and-designing-synthetic-biological-circuits-dongju-lim/
LOCATION:Daejeon
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20250404T110000
DTEND;TZID=Asia/Seoul:20250404T120000
DTSTAMP:20260422T145735
CREATED:20250217T080308Z
LAST-MODIFIED:20250217T080308Z
UID:10771-1743764400-1743768000@www.ibs.re.kr
SUMMARY:A lognormal Poisson model for single cell transcriptomic normalization - Fred Wright
DESCRIPTION:Abstract \nThe advent of single-cell transcriptomics has brought a greatly improved understanding of the heterogeneity of gene expression across cell types\, with important applications in developmental biology and cancer research. Single-cell RNA sequencing datasets\, which are based on tags called universal molecular identifiers\, typically include a large number of zeroes. For such datasets\, genes with even moderate expression may be poorly represented in sequencing count matrices. Standard pipelines often retain only a small subset of genes for further analysis\, but we address the problem of estimating relative expression across the entire transcriptome by adopting a multivariate lognormal Poisson count model. We propose empirical Bayes estimation procedures to estimate latent cell-cell correlations\, and to recover meaningful estimates for genes with low expression. For small groups of cells\, an important sampling procedure uses the full cell-cell correlation structure and is computationally feasible. For larger datasets\, we propose a gene-level shrinkage procedure that has favorable performance for datasets with approximately compound symmetric cell-cell correlation. A fast procedure that incorporates matrix approximations is also promising\, and extensible to very large datasets. We apply our approaches to simulated and real datasets\, and demonstrate favorable performance in comparisons to competing normalization approaches. We further illustrate the applications of our approach in downstream analyses\, including cell-type clustering and identification. \n 
URL:https://www.ibs.re.kr/bimag/event/a-lognormal-poisson-model-for-single-cell-transcriptomic-normalization-fred-wright/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/png:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2025/02/Fred_wright-e1739779380180.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20250328T140000
DTEND;TZID=Asia/Seoul:20250328T160000
DTSTAMP:20260422T145735
CREATED:20250302T133447Z
LAST-MODIFIED:20250327T010923Z
UID:10853-1743170400-1743177600@www.ibs.re.kr
SUMMARY:Frequency-Dependent Covariance Reveals Critical Spatiotemporal Patterns of Synchronized Activity in the Human Brain - Hyun Kim
DESCRIPTION:In this talk\, we discuss the paper “Frequency-Dependent Covariance Reveals Critical Spatiotemporal Patterns of Synchronized Activity in the Human Brain” by Rubén Calvo et al.\, Physical Review Letters 2024\, at the Journal Club. \nAbstract \nRecent analyses\, leveraging advanced theoretical techniques and high-quality data from thousands of simultaneously recorded neurons across regions in the brain\, compellingly support the hypothesis that neural dynamics operate near the edge of instability. However\, these and related analyses often fail to capture the intricate temporal structure of brain activity\, as they primarily rely on time-integrated measurements across neurons. Here\, we present a novel framework designed to explore signatures of criticality across diverse frequency bands and construct a much more comprehensive description of brain activity. Furthermore\, we introduce a method for projecting brain activity onto a basis of spatiotemporal patterns\, facilitating time-dependent dimensionality reduction. Applying this framework to a magnetoencephalography dataset\, we observe significant differences in criticality signatures\, effective dimensionality\, and spatiotemporal activity patterns between healthy subjects and individuals with Parkinson’s disease\, highlighting its potential impact.
URL:https://www.ibs.re.kr/bimag/event/journal-club-hyun-kim/
LOCATION:Daejeon
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20250328T110000
DTEND;TZID=Asia/Seoul:20250328T120000
DTSTAMP:20260422T145735
CREATED:20250217T075911Z
LAST-MODIFIED:20250217T081432Z
UID:10766-1743159600-1743163200@www.ibs.re.kr
SUMMARY:Dynamics and Decision Making in Single Cells - Galit Lahav
DESCRIPTION:Abstract \nIndividual human cancer cells often show different responses to the same treatment. In this talk I will share the quantitative experimental approaches my lab has developed for studying the fate and behavior of human cells at the single-cell level. I will focus on the tumor suppressor protein p53\, a transcription factor controlling genomic integrity and cell survival. In the last several years we have established the dynamics of p53 (changes in its levels over time) as an important mechanism controlling gene expression and guiding cellular outcomes. I will present recent studies from the lab demonstrating how studying p53 dynamics in response to radiation and chemotherapy in single cells can guide the design and schedule of combinatorial therapy\, and how the p53 oscillator can be used to study the principles and function of entertainment in Biology. I will also present new findings suggesting that p53’s post-translational modification state is altered between its first and second pulses of expression\, and the effects these have on gene expression programs over time.
URL:https://www.ibs.re.kr/bimag/event/dynamics-and-decision-making-in-single-cells-galit-lahav/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/png:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2025/02/Galit-Lahav-e1739779209180.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20250321T143000
DTEND;TZID=Asia/Seoul:20250321T163000
DTSTAMP:20260422T145735
CREATED:20250226T070501Z
LAST-MODIFIED:20250314T140235Z
UID:10811-1742567400-1742574600@www.ibs.re.kr
SUMMARY:Designing microplastic-binding peptides with a variational quantum circuit–based hybrid quantum-classical approach - Gyuyoung Hwang
DESCRIPTION:In this talk\, we discuss the paper “Designing microplastic-binding peptides with a variational quantum circuit–based hybrid quantum-classical approach” by R.C. Vendrell et.al.\, Sci. Adv. 2024 at the Journal Club. \nAbstract \nDe novo peptide design exhibits great potential in materials engineering\, particularly for the use of plastic-binding peptides to help remediate microplastic pollution. There are no known peptide binders for many plastics—a gap that can be filled with de novo design. Current computational methods for peptide design exhibit limitations in sampling and scaling that could be addressed with quantum computing. Hybrid quantum-classical methods can leverage complementary strengths of near-term quantum algorithms and classical techniques for complex tasks like peptide design. This work introduces a hybrid quantum-classical generative framework for designing plastic-binding peptides combining variational quantum circuits with a variational autoencoder network. We demonstrate the framework’s effectiveness in generating peptide candidates\, evaluate its efficiency for property-oriented design\, and validate the candidates with molecular dynamics simulations. This quantum computing–based approach could accelerate the development of biomolecular tools for environmental and biomedical applications while advancing the study of biomolecular systems through quantum technologies. \n 
URL:https://www.ibs.re.kr/bimag/event/phantom-oscillations-in-principal-component-analysis-gyuyoung-hwang/
LOCATION:Daejeon
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20250321T110000
DTEND;TZID=Asia/Seoul:20250321T120000
DTSTAMP:20260422T145735
CREATED:20250217T075507Z
LAST-MODIFIED:20250217T075934Z
UID:10756-1742554800-1742558400@www.ibs.re.kr
SUMMARY:Disrupting Heathcare Using Deep Data and Remote Monitoring - Michael Snyder
DESCRIPTION:Abstract \nOur present healthcare system focuses on treating people when they are ill rather than keeping them healthy. We have been using big data and remote monitoring approaches to monitor people while they are healthy to keep them that way and detect disease at its earliest moment presymptomatically. We use advanced multiomics technologies (genomics\, immunomics\, transcriptomics\, proteomics\, metabolomics\, microbiomics) as well as wearables and microsampling for actively monitoring health. Following a group of 109 individuals for over 13 years revealed numerous major health discoveries covering cardiovascular disease\, oncology\, metabolic health and infectious disease. We have also found that individuals have distinct aging patterns that can be measured in an actionable period of time. Finally\, we have used wearable devices for early detection of infectious disease\, including COVID-19 as well as microsampling for monitoring and improving lifestyle. We believe that advanced technologies have the potential to transform healthcare and keep people healthy.
URL:https://www.ibs.re.kr/bimag/event/disrupting-heathcare-using-deep-data-and-remote-monitoring-michael-snyder/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2025/02/mike-snyder-e1739778881131.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20250314T140000
DTEND;TZID=Asia/Seoul:20250314T160000
DTSTAMP:20260422T145735
CREATED:20250226T070011Z
LAST-MODIFIED:20250226T070011Z
UID:10806-1741960800-1741968000@www.ibs.re.kr
SUMMARY:A biological model of nonlinear dimensionality reduction - Shingo Gibo
DESCRIPTION:In this talk\, we discuss the paper “A biological model of nonlinear dimensionality reduction” by K. Yoshida and T. Toyoizumi\, Science Advances\, 2025\, at the Journal Club. \nAbstract \nObtaining appropriate low-dimensional representations from high-dimensional sensory inputs in an unsupervised manner is essential for straightforward downstream processing. Although nonlinear dimensionality reduction methods such as t-distributed stochastic neighbor embedding (t-SNE) have been developed\, their implementation in simple biological circuits remains unclear. Here\, we develop a biologically plausible dimensionality reduction algorithm compatible with t-SNE\, which uses a simple three-layer feedforward network mimicking the Drosophila olfactory circuit. The proposed learning rule\, described as three-factor Hebbian plasticity\, is effective for datasets such as entangled rings and MNIST\, comparable to t-SNE. We further show that the algorithm could be working in olfactory circuits in Drosophila by analyzing the multiple experimental data in previous studies. We lastly suggest that the algorithm is also beneficial for association learning between inputs and rewards\, allowing the generalization of these associations to other inputs not yet associated with rewards.
URL:https://www.ibs.re.kr/bimag/event/a-biological-model-of-nonlinear-dimensionality-reduction-shingo-gibo/
LOCATION:Daejeon
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20250314T110000
DTEND;TZID=Asia/Seoul:20250314T120000
DTSTAMP:20260422T145735
CREATED:20250217T075146Z
LAST-MODIFIED:20250217T075146Z
UID:10749-1741950000-1741953600@www.ibs.re.kr
SUMMARY:COVID-19 and Challenges to the Classical Theory of Epidemics - Simon Levin
DESCRIPTION:Abstract \nThe standard theory of infectious diseases\, tracing back to the work of Kermack and McKendrick nearly a century ago\, has been a triumph of mathematical biology\, a rare marriage of theory and application. Yet the limitations of its most simple representations\, which has always been known\, have been laid bare in dealing with COVID-19\, sparking a spate of extensions of the basic theory to deal more effectively with aspects of viral evolution\, asymptotic stages\, heterogeneity of various kinds\, the ambiguities of notions of herd immunity\, the role of social behaviors and other features. This lecture will address some progress in addressing these\, and open challenges in expanding the mathematical theory.
URL:https://www.ibs.re.kr/bimag/event/covid-19-and-challenges-to-the-classical-theory-of-epidemics-simon-levin/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2025/02/simon-levin-e1739778689468.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20250307T140000
DTEND;TZID=Asia/Seoul:20250307T160000
DTSTAMP:20260422T145735
CREATED:20250226T065718Z
LAST-MODIFIED:20250305T000149Z
UID:10804-1741356000-1741363200@www.ibs.re.kr
SUMMARY:The Large Language Models on Biomedical Data Analysis: A Survey - Myna Lim
DESCRIPTION:In this talk\, we discuss the paper “The Large Language Models on Biomedical Data Analysis: A Survey” by Wei Lan et.al\, IEEE J. Biomedical and Health Informatics\, 2025\, at the Journal Club. \nAbstract  \nWith the rapid development of Large Language Model (LLM) technology\, it has become an indispensable force in biomedical data analysis research. However\, biomedical researchers currently have limited knowledge about LLM. Therefore\, there is an urgent need for a summary of LLM applications in biomedical data analysis. Herein\, we propose this review by summarizing the latest research work on LLM in biomedicine. In this review\, LLM techniques are first outlined. We then discuss biomedical datasets and frameworks for biomedical data analysis\, followed by a detailed analysis of LLM applications in genomics\, proteomics\, transcriptomics\, radiomics\, single-cell analysis\, medical texts and drug discovery. Finally\, the challenges of LLM in biomedical data analysis are discussed. In summary\, this review is intended for researchers interested in LLM technology and aims to help them understand and apply LLM in biomedical data analysis research.
URL:https://www.ibs.re.kr/bimag/event/machine-learning-model-for-menstrual-cycle-phase-classification-and-ovulation-day-detection-based-on-sleeping-heart-rate-under-free-living-conditions-myna-lim/
LOCATION:Daejeon
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20250306T130000
DTEND;TZID=Asia/Seoul:20250306T153000
DTSTAMP:20260422T145735
CREATED:20250226T071803Z
LAST-MODIFIED:20250226T072211Z
UID:10813-1741266000-1741275000@www.ibs.re.kr
SUMMARY:심리학이 알려주는 연구의 기술: 논리적 사고부터 논문 작성까지 - 서수연
DESCRIPTION:본 세미나에서는 성신여자대학교 서수연 교수님께서 “심리학이 알려주는 연구의 기술: 논리적 사고부터 논문 작성까지”라는 내용으로 강연을 해주실 예정입니다. \n  \n 
URL:https://www.ibs.re.kr/bimag/event/psychology-and-research/
LOCATION:Daejeon
CATEGORIES:Biomedical Mathematics Seminar
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20250228T140000
DTEND;TZID=Asia/Seoul:20250228T160000
DTSTAMP:20260422T145735
CREATED:20250220T082847Z
LAST-MODIFIED:20250225T080719Z
UID:10787-1740751200-1740758400@www.ibs.re.kr
SUMMARY:Quantifying information accumulation encoded in the dynamics of biochemical signaling - Kang Min Lee
DESCRIPTION:In this talk\, we discuss the paper “Quantifying information accumulation encoded in the dynamics of biochemical signaling” by Y. Tang\, et.al\, Nature Communications\, 2021. \nAbstract \nCellular responses to environmental changes are encoded in the complex temporal patterns of signaling proteins. However\, quantifying the accumulation of information over time to direct cellular decision-making remains an unsolved challenge. This is\, in part\, due to the combinatorial explosion of possible configurations that need to be evaluated for information in time-course measurements. Here\, we develop a quantitative framework\, based on inferred trajectory probabilities\, to calculate the mutual information encoded in signaling dynamics while accounting for cell-cell variability. We use it to understand NFκB transcriptional dynamics in response to different immune threats\, and reveal that some threats are distinguished faster than others. Our analyses also suggest specific temporal phases during which information distinguishing threats becomes available to immune response genes; one specific phase could be mapped to the functionality of the IκBα negative feedback circuit. The framework is generally applicable to single-cell time series measurements\, and enables understanding how temporal regulatory codes transmit information over time.
URL:https://www.ibs.re.kr/bimag/event/quantum-computing-enhanced-algorithm-unveils-potential-kras-inhibitors-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:20250221T140000
DTEND;TZID=Asia/Seoul:20250221T160000
DTSTAMP:20260422T145735
CREATED:20250128T024716Z
LAST-MODIFIED:20250203T004930Z
UID:10712-1740146400-1740153600@www.ibs.re.kr
SUMMARY:Constraining nonlinear time series modeling with the metabolic theory of ecology - Olive Cawiding
DESCRIPTION:In this talk\, we discuss the paper “Constraining nonlinear time series modeling with the metabolic theory of ecology” by S.B. Munch et.al.\, PNAS\, 2023. \nAbstract \nForecasting the response of ecological systems to environmental change is a critical challenge for sustainable management. The metabolic theory of ecology (MTE) posits scaling of biological rates with temperature\, but it has had limited application to population dynamic forecasting. Here we use the temperature dependence of the MTE to constrain empirical dynamic modeling (EDM)\, an equation-free nonlinear machine learning approach for forecasting. By rescaling time with temperature and modeling dynamics on a “metabolic time step\,” our method (MTE-EDM) improved forecast accuracy in 18 of 19 empirical ectotherm time series (by 19% on average)\, with the largest gains in more seasonal environments. MTE-EDM assumes that temperature affects only the rate\, rather than the form\, of population dynamics\, and that interacting species have approximately similar temperature dependence. A review of laboratory studies suggests these assumptions are reasonable\, at least approximately\, though not for all ecological systems. Our approach highlights how to combine modern data-driven forecasting techniques with ecological theory and mechanistic understanding to predict the response of complex ecosystems to temperature variability and trends.
URL:https://www.ibs.re.kr/bimag/event/constraining-nonlinear-time-series-modeling-with-the-metabolic-theory-of-ecology-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:20250214T140000
DTEND;TZID=Asia/Seoul:20250214T160000
DTSTAMP:20260422T145735
CREATED:20250128T024512Z
LAST-MODIFIED:20250203T004838Z
UID:10710-1739541600-1739548800@www.ibs.re.kr
SUMMARY:Method for cycle detection in sparse\, irregularly sampled\, long-term neuro-behavioral timeseries - Brenda Gavina
DESCRIPTION:In this talk\, we discuss the paper “Method for cycle detection in sparse\, irregularly sampled\, long-term neuro-behavioral timeseries: Basis pursuit denoising with polynomial detrending of long-term\, inter-ictal epileptiform activity” by Irena Balzekas et.al.\, Plos Com.\, 2024. \nAbstract \nNumerous physiological processes are cyclical\, but sampling these processes densely enough to perform frequency decomposition and subsequent analyses can be challenging. Mathematical approaches for decomposition and reconstruction of sparsely and irregularly sampled signals are well established but have been under-utilized in physiological applications. We developed a basis pursuit denoising with polynomial detrending (BPWP) model that recovers oscillations and trends from sparse and irregularly sampled timeseries. We validated this model on a unique dataset of long-term inter-ictal epileptiform discharge (IED) rates from human hippocampus recorded with a novel investigational device with continuous local field potential sensing. IED rates have well established circadian and multiday cycles related to sleep\, wakefulness\, and seizure clusters. Given sparse and irregular samples of IED rates from multi-month intracranial EEG recordings from ambulatory humans\, we used BPWP to compute narrowband spectral power and polynomial trend coefficients and identify IED rate cycles in three subjects. In select cases\, we propose that random and irregular sampling may be leveraged for frequency decomposition of physiological signals.
URL:https://www.ibs.re.kr/bimag/event/method-for-cycle-detection-in-sparse-irregularly-sampled-long-term-neuro-behavioral-timeseries-brenda-gavina/
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:20250207T140000
DTEND;TZID=Asia/Seoul:20250207T160000
DTSTAMP:20260422T145735
CREATED:20250128T024238Z
LAST-MODIFIED:20250206T103822Z
UID:10708-1738936800-1738944000@www.ibs.re.kr
SUMMARY:A cell atlas foundation model for scalable search of similar human cells - Kevin Spinicci
DESCRIPTION:In this talk\, we discuss the paper “A cell atlas foundation model for scalable search of similar human cells” by Graham Heimberg et.al.\, Nature\, 2024 at the Journal Club. \nAbstract \n\n\nSingle-cell RNA sequencing has profiled hundreds of millions of human cells across organs\, diseases\, development and perturbations to date. Mining these growing atlases could reveal cell–disease associations\, identify cell states in unexpected tissue contexts and relate in vivo biology to in vitro models. These require a common measure of cell similarity across the body and an efficient way to search. Here we develop SCimilarity\, a metric-learning framework to learn a unified and interpretable representation that enables rapid queries of tens of millions of cell profiles from diverse studies for cells that are transcriptionally similar to an input cell profile or state. We use SCimilarity to query a 23.4-million-cell atlas of 412 single-cell RNA-sequencing studies for macrophage and fibroblast profiles from interstitial lung disease1 and reveal similar cell profiles across other fibrotic diseases and tissues. The top scoring in vitro hit for the macrophage query was a 3D hydrogel system2\, which we experimentally demonstrated reproduces this cell state. SCimilarity serves as a foundation model for single-cell profiles that enables researchers to query for similar cellular states across the human body\, providing a powerful tool for generating biological insights from the Human Cell Atlas.
URL:https://www.ibs.re.kr/bimag/event/scdiffusion-conditional-generation-of-high-quality-single-cell-data-using-diffusion-model-kevin-spinicci/
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:20250131T140000
DTEND;TZID=Asia/Seoul:20250131T160000
DTSTAMP:20260422T145735
CREATED:20250126T021153Z
LAST-MODIFIED:20250203T004702Z
UID:10696-1738332000-1738339200@www.ibs.re.kr
SUMMARY:Self-supervised learning of accelerometer data provides new insights for sleep and its association with mortality - Yun Min Song
DESCRIPTION:In this talk\, we discuss the paper “Self-supervised learning of accelerometer data provides new insights for sleep and\nits association with mortality” by H. Yuan et.al\, npj digital medicine\, 2024\, at the Journal Club. \nAbstract  \nSleep is essential to life. Accurate measurement and classification of sleep/wake and sleep stages is important in clinical studies for sleep disorder diagnoses and in the interpretation of data from consumer devices for monitoring physical and mental well-being. Existing non-polysomnography sleep classification techniques mainly rely on heuristic methods developed in relatively small cohorts. Thus\, we aimed to establish the accuracy of wrist-worn accelerometers for sleep stage classification and subsequently describe the association between sleep duration and efficiency (proportion of total time asleep when in bed) with mortality outcomes. We developed a self-supervised deep neural network for sleep stage classification using concurrent laboratory-based polysomnography and accelerometry. After exclusion\, 1113 participant nights of data were used for training. The difference between polysomnography and the model classifications on the external validation was 48.2 min (95% limits of agreement (LoA): −50.3 to 146.8 min) for total sleep duration\, −17.1 min for REM duration (95% LoA: −56.7 to 91.0 min) and 31.1 min (95% LoA: −67.3 to 129.5 min) for NREM duration. The sleep classifier was deployed in the UK Biobank with ~100\,000 participants to study the association of sleep duration and sleep efficiency with all-cause mortality. Among 66\,262 UK Biobank participants\, 1644 mortality events were observed. Short sleepers (<6 h) had a higher risk of mortality compared to participants with normal sleep duration 6–7.9 h\, regardless of whether they had low sleep efficiency (Hazard ratios (HRs): 1.36; 95% confidence intervals (CIs): 1.18 to 1.58) or high sleep efficiency (HRs: 1.29; 95% CIs: 1.04–1.61). Deep-learning-based sleep classification using accelerometers has a fair to moderate agreement with polysomnography. Our findings suggest that having short overnight sleep confers mortality risk irrespective of sleep continuity.
URL:https://www.ibs.re.kr/bimag/event/self-supervised-learning-of-accelerometer-data-provides-new-insights-for-sleep-and-its-association-with-mortality-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:20250124T140000
DTEND;TZID=Asia/Seoul:20250124T160000
DTSTAMP:20260422T145735
CREATED:20250104T005711Z
LAST-MODIFIED:20250104T005711Z
UID:10531-1737727200-1737734400@www.ibs.re.kr
SUMMARY:Plausible\, robust biological oscillations through allelic buffering - Eui Min Jeong
DESCRIPTION:In this talk\, we discuss the paper “Plausible\, robust biological oscillations through allelic buffering” by F-S. Hsieh et.al\, Cell Systems\, 2024. at the Journal Club.  \nAbstract \nBiological oscillators can specify time- and dose-dependent functions via dedicated control of their oscillatory dynamics. However\, how biological oscillators\, which recurrently activate noisy biochemical processes\, achieve robust oscillations remains unclear. Here\, we characterize the long-term oscillations of p53 and its negative feedback regulator Mdm2 in single cells after DNA damage. Whereas p53 oscillates regularly\, Mdm2 from a single MDM2 allele exhibits random unresponsiveness to ∼9% of p53 pulses. Using allelic-specific imaging of MDM2 activity\, we show that MDM2 alleles buffer each other to maintain p53 pulse amplitude. Removal of MDM2 allelic buffering cripples the robustness of p53 amplitude\, thereby elevating p21 levels and cell-cycle arrest. In silico simulations support that allelic buffering enhances the robustness of biological oscillators and broadens their plausible biochemical space. Our findings show how allelic buffering ensures robust p53 oscillations\, highlighting the potential importance of allelic buffering for the emergence of robust biological oscillators during evolution. A record of this paper’s transparent peer review process is included in the supplemental information. 
URL:https://www.ibs.re.kr/bimag/event/plausible-robust-biological-oscillations-through-allelic-buffering-eui-min-jeong/
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:20250114T110000
DTEND;TZID=Asia/Seoul:20250114T120000
DTSTAMP:20260422T145735
CREATED:20241231T015243Z
LAST-MODIFIED:20250109T125003Z
UID:10499-1736852400-1736856000@www.ibs.re.kr
SUMMARY:Biomolecular Condensates: Principles and Models\, Jeong-Mo Choi
DESCRIPTION: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 and harness them as tools for engineering cellular processes in synthetic biology. In this talk\, I will discuss the key principles that govern the behaviors of biomolecular condensates and introduce several (semi-)analytical models that provide both qualitative insights and quantitative predictions. These models serve as a foundation for understanding and leveraging condensate-driven phenomena in biological systems.
URL:https://www.ibs.re.kr/bimag/event/tbd-jeong-mo-choi/
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:20250110T140000
DTEND;TZID=Asia/Seoul:20250110T160000
DTSTAMP:20260422T145735
CREATED:20250104T003730Z
LAST-MODIFIED:20250107T122054Z
UID:10529-1736517600-1736524800@www.ibs.re.kr
SUMMARY:CARE as a wearable derived feature linking circadian amplitude to human cognitive functions - Dongju Lim
DESCRIPTION:In this talk\, we discuss the paper “CARE as a wearable derived feature linking circadian amplitude to human cognitive functions” by Shuya Cui et.al.\, npj Digital Medicine\, 2023. \nAbstract \nCircadian rhythms are crucial for regulating physiological and behavioral processes. Pineal hormone melatonin is often used to measure circadian amplitude but its collection is costly and time-consuming. Wearable activity data are promising alternative\, but the most commonly used measure\, relative amplitude\, is subject to behavioral masking. In this study\, we firstly derive a feature named circadian activity rhythm energy (CARE) to better characterize circadian amplitude and validate CARE by correlating it with melatonin amplitude (Pearson’s r = 0.46\, P = 0.007) among 33 healthy participants. Then we investigate its association with cognitive functions in an adolescent dataset (Chinese SCHEDULE-A\, n = 1703) and an adult dataset (UK Biobank\, n = 92\,202)\, and find that CARE is significantly associated with Global Executive Composite (β = 30.86\, P = 0.016) in adolescents\, and reasoning ability\, short-term memory\, and prospective memory (OR = 0.01\, 3.42\, and 11.47 respectively\, all P < 0.001) in adults. Finally\, we identify one genetic locus with 126 CARE-associated SNPs using the genome-wide association study\, of which 109 variants are used as instrumental variables in the Mendelian Randomization analysis\, and the results show a significant causal effect of CARE on reasoning ability\, short-term memory\, and prospective memory (β = -59.91\, 7.94\, and 16.85 respectively\, all P < 0.0001). The present study suggests that CARE is an effective wearable-based metric of circadian amplitude with a strong genetic basis and clinical significance\, and its adoption can facilitate future circadian studies and potential intervention strategies to improve circadian rhythms and cognitive functions.
URL:https://www.ibs.re.kr/bimag/event/mapping-the-physiological-changes-in-sleep-regulation-across-infancy-and-young-childhood-dongju-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:20250103T140000
DTEND;TZID=Asia/Seoul:20250103T160000
DTSTAMP:20260422T145735
CREATED:20250101T061847Z
LAST-MODIFIED:20250101T061847Z
UID:10503-1735912800-1735920000@www.ibs.re.kr
SUMMARY:Feature selection and dimension reduction for single-cell RNA-Seq based on a multinomial model - Seokhwan Moon
DESCRIPTION:In this talk\, we discuss the paper “Feature selection and dimension reduction for single-cell RNA-Seq based on a multinomial model” by F. W. Townes et.al.\, Genome Biology\, 2019. \nAbstract  \nSingle-cell RNA-Seq (scRNA-Seq) profiles gene expression of individual cells. Recent scRNA-Seq datasets have incorporated unique molecular identifiers (UMIs). Using negative controls\, we show UMI counts follow multinomial sampling with no zero inflation. Current normalization procedures such as log of counts per million and feature selection by highly variable genes produce false variability in dimension reduction. We propose simple multinomial methods\, including generalized principal component analysis (GLM-PCA) for non-normal distributions\, and feature selection using deviance. These methods outperform the current practice in a downstream clustering assessment using ground truth datasets.
URL:https://www.ibs.re.kr/bimag/event/feature-selection-and-dimension-reduction-for-single-cell-rna-seq-based-on-a-multinomial-model-seokhwan-moon/
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:20241230T110000
DTEND;TZID=Asia/Seoul:20241230T120000
DTSTAMP:20260422T145735
CREATED:20241222T065319Z
LAST-MODIFIED:20241222T065404Z
UID:10424-1735556400-1735560000@www.ibs.re.kr
SUMMARY:Enhanced Gaussian Process Surrogates for Optimization and Sampling by Pure Exploration - Hwanwoo Kim
DESCRIPTION:Abstract: \nIn 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. Furthermore\, to facilitate Bayesian inference with an intractable likelihood\, we propose to utilize the optimization iterates as design points to build a Gaussian process surrogate model for the unnormalized log-posterior density. We provide bounds for the Hellinger distance between the true and the approximate posterior distributions in terms of the number of design points. The effectiveness of our algorithms is demonstrated in benchmark non-convex test functions for optimization\, and in a black-box engineering design problem. We also showcase the effectiveness of our posterior approximation approach in Bayesian inference for parameters of dynamical systems.
URL:https://www.ibs.re.kr/bimag/event/enhanced-gaussian-process-surrogates-for-optimization-and-sampling-by-pure-exploration-hwanwoo-kim/
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:20241227T100000
DTEND;TZID=Asia/Seoul:20241227T120000
DTSTAMP:20260422T145735
CREATED:20241022T001840Z
LAST-MODIFIED:20241226T235355Z
UID:10197-1735293600-1735300800@www.ibs.re.kr
SUMMARY:Diffusion Posterior Sampling for Linear Inverse Problem Solving- A Filtering Perspective - U Jin Choi
DESCRIPTION:In this talk\, we discuss the paper : “Diffusion Posterior Sampling for Linear Inverse Problem Solving- A Filtering Perspective” by Z. Dou& Y. Song \n\n\nDiffusion 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 Bayesian posterior sampling. However\, exact posterior sampling for diffusion models is intractable. Current solutions often hinge on approximations that are either computationally expensive or lack strong theoretical guarantees. In this work\, we introduce an efficient diffusion sampling algorithm for linear inverse problems that is guaranteed to be asymptotically accurate. We reveal a link between Bayesian posterior sampling and Bayesian filtering in diffusion models\, proving the former as a specific instance of the latter. Our method\, termed filtering posterior sampling\, leverages sequential Monte Carlo methods to solve the corresponding filtering problem. It seamlessly integrates with all Markovian diffusion samplers\, requires no model re-training\, and guarantees accurate samples from the Bayesian posterior as particle counts rise. Empirical tests demonstrate that our method generates better or comparable results than leading zero-shot diffusion posterior samplers on tasks like image inpainting\, super-resolution\, and deblurring.
URL:https://www.ibs.re.kr/bimag/event/diffusion-posterior-sampling-for-linear-inverse-problem-solving-a-filtering-perspective-u-jin-choi/
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
END:VCALENDAR