Week 19.01.2026 – 25.01.2026

Our bodies are composed of many distinct cell types, each thought to correspond to an attractor state of an underlying high-dimensional regulatory network. Yet, we lack an explicit bottom-up mathematical theory linking molecular mechanisms to observed cell identity dynamics. I will introduce a mechanistic theoretical model that explains how regulatory interactions generate and control an effective high-dimensional landscape for cell identity. Inspired by dense associative memory models, the framework describes how transcription factors couple through shared chromatin modulation, leading to multistability, hierarchical organisation of cell identities, and controlled transitions between states. The model quantitatively predicts cell fate reprogramming outcomes and reconstructs the differentiation structure of haematopoiesis, including progenitor states and bifurcations, without fitting unobserved parameters. More broadly, the framework explains how molecular perturbations reshape the landscape in both normal and cancer cells, connecting molecular regulation to systems-level control of cell identity.