Events

In this talk, we discuss the paper "GenAI-Net: A Generative AI Framework for Automated Biomolecular Network Design" by M. Filo et al., arxiv, 2026. Abstract Biomolecular networks underpin emerging technologies in synthetic biology—from robust biomanufacturing and metabolic engineering to smart therapeutics and cell-based diagnostics—and also provide a mechanistic language for understanding complex dynamics in natural …

In this talk, we discuss the paper "TwinCell: Large Causal Cell Model for Reliable and Interpretable Therapeutic Target Prioritisation" by J.-B. Morlot et al., bioarxiv, 2026. Abstract Drug discovery is impeded by the difficulty of translating targets from preclinical models to patients. Here, we present TwinCell, a Large Causal Cell Model (LCCM) capable of generalising …

In this talk, we discuss the paper "A multimodal sleep foundation model for disease prediction" by Rahul Thapa et al., Nature Medicine, 2026. Abstract Sleep is a fundamental biological process with broad implications for physical and mental health, yet its complex relationship with disease remains poorly understood. Polysomnography (PSG)—the gold standard for sleep analysis—captures rich …

In this talk, we discuss the paper "Temporal tissue dynamics from a spatial snapshot" by Jonathan Somer et al., Nature, 2026. Abstract Physiological and pathological processes such as inflammation and cancer emerge from interactions between cells over time1. However, methods to follow cell populations over time within the native context of a human tissue are …

In this talk, we discuss the paper "A multi-agent reinforcement learning framework for exploring dominant strategies in iterated and evolutionary games" by Qi Su et al., Nat. Comm., 2026. Abstract Exploring dominant strategies in iterated games holds theoretical and practical significance across diverse domains. Previous studies, through mathematical analysis of limited cases, have unveiled classic …

In this tallk, we discuss the paper "Discovering network dynamics with neural symbolic regression" by Zihan Yu et al., Nature Com. Science, 2026. Abstract Network dynamics are fundamental to analyzing the properties of high-dimensional complex systems and understanding their behavior. Despite the accumulation of observational data across many domains, mathematical models exist in only a …

In this tallk, we discuss the paper “Foundation Models for Wearable Movement Data in Mental Health Research” by Franklin Y. Ruan et al., arXiv, 2025. Abstract Pretrained foundation models and transformer architectures have driven the success of large language models (LLMs) and other modern AI breakthroughs. However, similar advancements in health data modeling remain limited …

In this talk, we discuss the paper “Digital biomarkers for brain health: passive and continuous assessment from wearable sensors” by Igor Matias et al., npj digital medicine, 2026. Abstract Continuous and scalable monitoring of cognition and affective states is critical for the early detection of brain health, which is currently limited by the burden of …