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. Abstract Recent analyses, leveraging advanced theoretical techniques and high-quality data from thousands of simultaneously recorded neurons across regions in the brain, compellingly …

In this talk, we discuss the paper "Accurate predictions on small data with a tabular foundation model" by Noah Hollmann et al., Nature (2025). Abstract Tabular 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 …

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. Abstract  The 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 …

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. Abstract  Transfer entropy (TE) is a widely used tool for quantifying causal relationships in stochastic dynamical systems. Traditionally, TE and its conditional …

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 …