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 …

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 …

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 …

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 …

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 …