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  • Physics-constrained neural ordinary differential equation models to discover and predict microbial community dynamics – Kang Min Lee

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

    In this talk, we discuss the paper "Physics-constrained neural ordinary differential equation models to discover and predict microbial community dynamics" by J. Thompson et al., bioarxiv, 2025. Abstract Microbial communities play essential roles in shaping ecosystem functions and predictive modeling frameworks are crucial for understanding, controlling, and harnessing their properties. Competition and cross-feeding of metabolites …

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  • Decomposing causality into its synergistic, unique, and redundant components – Olive Cawiding

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

    In this talk, we discuss the paper "Decomposing causality into its synergistic, unique, and redundant components" by Álvaro Martínez-Sánchez et al., Nature Communications, 2024. Abstract Causality lies at the heart of scientific inquiry, serving as the fundamental basis for understanding interactions among variables in physical systems. Despite its central role, current methods for causal inference …

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  • SCassist: An AI Based Workflow Assistant for Single-Cell Analysis – Aqsa Awan

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

    In this talk, we discuss the paper "SCassist: An AI Based Workflow Assistant for Single-Cell Analysis " by Vijayaraj Nagarajan et al., bioarxiv, 2025.  Abstract Single-cell RNA sequencing (scRNA-seq) data analysis often involves complex iterative workflow, requiring significant expertise and time. To navigate this complexity, we have developed SCassist, an R package that leverages the power …

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  • Sleep as part of the 24-hour day: Methods and Applications in Oncology – Joshua Wiley

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

    Abstract Sleep is commonly analysed as an independent factor. However, because of the 24-hour constraints on a day, changes in sleep will co-occur with changes in remaining time use. This talk introduces compositional data analysis (CoDA) for sleep research. CoDA is illustrated using 24-hour sleep and activity data from accelerometry, first cross-sectionally showing associations between …

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  • Tackling inter-subject variability in smartwatch data using factorization models – Myna Lim

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

    In this talk, we discuss the paper "Tackling inter-subject variability in smartwatch data using factorization models" by Arman Naseri et. al, Scientific Reports, 2025. Abstract Smartwatches enable longitudinal and continuous data acquisition. This has the potential to remotely monitor (changes) of the health of users. However, differences among subjects (inter-subject variability) limit a model to …

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  • Excess Mortality, Two Lenses : Healthcare Access and Cross-National Time Trends – Daeil Jang

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

    Abstract Background : Excess mortality captures both the direct and indirect impacts of the pandemic. We examine (1) within-country heterogeneity by healthcare access over distinct viral waves in Korea, and (2) cross-country associations between excess mortality and preparedness (Global Health Security, GHS), stratified by IMF development stage. Methods : Study 1 assembled a region-level panel …

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  • Topological Data Analysis for Multiscale Biology – Heather Harrington

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

    Abstract Many processes in the life sciences are inherently multi-scale and dynamic. Spatial structures and patterns vary across levels of organisation, from molecular to multi-cellular to multi-organism. With more sophisticated mechanistic models and data available, quantitative tools are needed to study their evolution in space and time. Topological data analysis (TDA) provides a multi-scale summary …

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  • Developing time-series machine learning methods to unlock new insights from large-scale biomedical resources – Aiden Doherty

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

    Abstract Smartphones and wearable devices provide a major opportunity to transform our understanding of the mechanisms, determinants, and consequences of diseases. For example, around 9 in 10 people own a smartphone in the United Kingdom, while one-fifth of US adults own wearable technologies. This high level of device ownership means that many people could contribute …

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  • Simulating the Spread of Infection in Networks with Quantum Computers – Shingo Gibo

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

    In this talk, we discuss the paper "Simulating the Spread of Infection in Networks with Quantum Computers" by Xiaoyang Wang, Yinchenguang Lyu, Changyu Yao and Xiao Yuan, Physical Review Applied, vol.19, 064035 (2023). Abstract We propose to use quantum computers to simulate infection spreading in networks. We first show the analogy between the infection distribution …

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  • Dynamical Mean-Field Theory of Complex Systems on Sparse Directed Networks – Gyuyoung Hwang

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

    In this talk, we discuss the paper "Dynamical Mean-Field Theory of Complex Systems on Sparse Directed Networks" by Fernando L. Metz, Phys. Rev. Letters, 2025. Abstract Although real-world complex systems typically interact through sparse and heterogeneous networks, analytic solutions of their dynamics are limited to models with all-to-all interactions. Here, we solve the dynamics of …

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  • Dynamical data science and AI for Biology and Medicine – Luonan Chen

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

    Abstract I will present a talk on "Dynamical data science and AI" for quantifying dynamical biological processes, disease progressions and various phenotypes, including dynamic network biomarkers (DNB) for early-warning signals of critical transitions, spatial-temporal information (STI) transformation for short-term time-series prediction, knockoff conditional mutual information (KOCMI) for quantifying interventional causality, partial cross-mapping (PCM) for causal …

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  • Dosing Time of Day Impacts the Safety of Antiarrhythmic Drugs in a Computational Model of Cardiac Electrophysiology – Chitaranjan Mahapatra

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

    In this talk, we discuss the paper "Dosing Time of Day Impacts the Safety of Antiarrhythmic Drugs in a Computational Model of Cardiac Electrophysiology" by Ning Wei and Casey O Diekman, J. Biol. Rhythms, 2025.  Abstract Circadian clocks regulate many aspects of human physiology, including cardiovascular function and drug metabolism. Administering drugs at optimal times of …

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