Boolean modelling as a logic-based dynamic approach in systems medicine – Kevin Spinicci

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). Abstract  Molecular mechanisms of health and disease are often represented as systems biology diagrams, and the coverage of such representation constantly increases. These static diagrams can

Chaos is not rare in natural ecosystems – Olive Cawiding

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

In this talk, we discuss the paper "Chaos is not rare in natural ecosystems" by Tanya L. Rogers, Bethany J. Johnson, and Stephan B. Munch, nature ecology & evolution, 2022. Abstract Chaotic dynamics are thought to be rare in natural populations but this may be due to methodological and data limitations, rather than the inherent

Quantifying and correcting bias in transcriptional parameter inference from single-cell data – Kangmin Lee

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

In this talk, we discuss the paper "Quantifying and correcting bias in transcriptional parameter inference from single-cell data" by Ramon Grima and Pierre-Marie Esmenjaud, Biophysical journal, 2024. Abstract The snapshot distribution of mRNA counts per cell can be measured using single-molecule fluorescence in situ hybridization or single-cell RNA sequencing. These distributions are often fit to the steady-state

Simplified descriptions of stochastic oscillators – Benjamin Lindner

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

Abstract Many 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

Large language models for scientific discovery in molecular property prediction – Aqsa Awan

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

In this talk, we discuss the paper "Large language models for scientific discovery in molecular property prediction" by Yizhen Zheng et.al., nature machine intelligence, 2025. Abstract Large language models (LLMs) are a form of artificial intelligence system encapsulating vast knowledge in the form of natural language. These systems are adept at numerous complex tasks including

Koopman operator approach to complex rhythmic systems – Hiroya Nakao

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

Abstract Spontaneous 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

Data splitting to avoid information leakage with DataSAIL – Myna Lim

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

In this talk, we discuss the paper, "Data splitting to avoid information leakage with DataSAIL" by Roman Joeres, et al., Nature Communications, 2025. Abstract Information leakage is an increasingly important topic in machine learning research for biomedical applications. When information leakage happens during a model’s training, it risks memorizing the training data instead of learning

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IBS Biomedical Mathematics Group (BIMAG)
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