Lucas Böttcher

The paper introduces BINODEs, a neural-ODE framework that integrates biochemical knowledge into dynamical models to improve interpretability and flexibility in modeling biochemical systems.

This paper introduces an END-nSDE framework to reconstruct noisy gene regulation dynamics from heterogeneous cell populations, outperforming RNNs and LSTMs in modeling extrinsic noise effects.

This paper introduces dynamics-informed neural-network controllers for medical digital twins and benchmarks them against other methods using agent-based models.

The paper quantifies the publicness or privateness of T and B cell clones using information-theoretic metrics applied to synthetic and empirical TCR data.