In recent years, there has been a revolution in the capability to measure and observe the processes of life on many temporal and spatial scales. Simultaneously, our ability to perform extensive simulations of molecular, cellular, and tissue-scale processes has substantially improved and will continue to do so. Research at ZIB is focused on extending this expertise towards spatiotemporal modeling and simulation across the molecular and cellular scales, from pushing time-scale and accuracy barriers, via a combination of the development of novel theoretical and algorithmic techniques for effective molecular or particle dynamics with machine learning, to spatio-temporal hybrid models coupling molecular with extra- and intra-cellular processes. Our projects target seamless integration of new mathematical approaches with incorporation of experimental data, high performance computing, and/or large-scale data analysis, and contribute to finding new strategies in relevant real-world applications like drug design or neurotransmission.
Model-Regularized Learning Of Complex Dynamical Behavior
This project is planned to couple machine learning approaches, especially from the field of Deep Learning, with (reduced) ODE models in the sense that the model becomes...
Model-Regularized Learning Of Complex Dynamical Behavior
Geometric Learning for Single-Cell RNA Velocity Modeling
Recent advances in Single-Cell RNA sequencing allow to infer both the gene expression of a cell and the so-called "velocity vector" initializing the changes in that...
Geometric Learning for Single-Cell RNA Velocity Modeling
AA1-19 Drug Candidates as Pareto Optima in Chemical Space
The search for novel drug candidates that, at the same time, act with high efficacy, comply with defined chemical properties, and also show low off-target effects can be...
AA1-19 Drug Candidates as Pareto Optima in Chemical Space
Opinion Dynamics
The literature contains a manifold of fundamental models for the dynamical changes of opinions through social influence during social interaction (personal, social...
Opinion Dynamics
Manifold-Valued Graph Neural Networks
Geometry-aware, data-analytic approaches improve understanding and assessment of pathophysiological processes. We will derive a new theoretical framework for deep neural...
Manifold-Valued Graph Neural Networks
Individualized Morphological Analysis of the Human Spine
The causes of low back pain are not yet fully understood. One essential part of a better understanding is the knowledge about the relationship between spinal morphology...
Individualized Morphological Analysis of the Human Spine
MODAL-MedLab
Changes in cells while they are undergoing transformation from "normal" to malignant cells (e.g. during infections) happen on many biological levels, such as genome...
MODAL-MedLab
Reduced Basis Methods in Orthopedic Hip Surgery Planning
This project aims at the development, analysis and implementation of algorithms for computer-assisted planning in hip surgery and hip joint replacement by fast virtual...
Reduced Basis Methods in Orthopedic Hip Surgery Planning
Research Campus MODAL
The Forschungscampus ("Research Campus") MODAL is a platform for a public-private innovation partnership established by ZIB and Freie Universität Berlin together with...
Research Campus MODAL
