Computational research and data science are revolutionizing the field of medicine. ZIB covers a broad range of activities such as the development of novel methods for enabling the simulation and prediction of drug interactions, allowing for more efficient and targeted drug design processes, or of the design of new techniques for analyzing vast amounts of biological and clinical data to uncover patterns, predict disease outcomes, and identify potential drug targets. Furthermore, our researchers are involved in the development of personalized medicine by integrating patient-specific data to tailor treatments, optimize healthcare outcomes, and enhance overall patient care in the realm of digital health.

Convex optimisation for generalised camera

Non-rigid shape registration

This research explores convex optimization for deformable registration of 3D templates to 2D image data from multiple cameras, with the generalized projection model. 

Non-rigid shape registration
Model-regularized Learning of Complex Dynamical Behavior

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
MATH+ AA1-20

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
Pareto-ML-Optimization-Cycle

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
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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
Spine_DYN3M

Individualized Morphological Analysis of the Human Spine

The causes of lower back pain (LBP) are still not fully understood. One essential part of a better understanding might be the association of LBP,  spinal morphology, and...

Individualized Morphological Analysis of the Human Spine
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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
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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
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Geometric Analysis of the Human Spine for image-based diagnosis, biomechanical analysis, and neurosurgery

Within Spine-Analysis project, articulated shape models of the human spine for surgeon planning are developed. In cooperation with the Medical Center of the Johannes...

Geometric Analysis of the Human Spine for image-based diagnosis, biomechanical analysis, and neurosurgery
MODAL

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