Forschung

Computational tools such as Molecular Dynamics (MD) have revolutionized the way we study biomolecules; however, they are severely limited by the computational cost of running simulations on biological time- and length-scales. Various coarse-grained (CG) models have been developed which rely on simpler representations of molecular systems than atomistic MD. While these models are difficult to configure using physical intuition, we have shown that by using state-of-the-art machine learning methods, it is possible to design accurate and efficient CG models which can correctly reproduce protein dynamics. By enhancing both our training dataset and network architecture, we hope to produce a “universal” CG model to study biological systems.

In this project the goal is to use algorithms to predict classes of the library classification system “Basisklassifikation” (which can be translated as basic classification). A library classification system is a taxonomy of predefined classes that represent disciplines, subdisciplines, themes or types of publications. Subject librarians assign one or more of these classes to each publication, allowing both final users or retrieval system to use this annotated information for finding publications. As input data we observe mainly bibliographic data, such as for example the title, the name of the publisher, the year of publication and the language of the publication. The algorithms should suggest several classes, which are then analyzed by

Aerosol-cloud interactions (ACI) are among the most uncertain processes in numerical weather prediction models. The effects of aerosols on clouds and precipitation vary significantly depending on the cloud type. Generally, high aerosol concentrations are assumed to activate more aerosol particles as cloud condensation nuclei (CCN), resulting in a larger number of smaller cloud droplets. This smaller droplet size suppresses the onset of precipitation in warm clouds by reducing the collision-coalescence process, leading to longer cloud lifetimes. Under polluted conditions, the increased water load at the freezing level can release additional latent heat, potentially invigorating convective clouds and enhancing rainfall. However, recent

Getting the signal across:
A crucial part of cellular physiology is the ability to transmit a variety of stimuli from outside the cell into the cell, triggering the right cellular response to the right stimuli. G-protein-coupled receptors (GPCRs) are a superfamily of proteins evolved precisely for this. Embedded on the cellular membrane, they sense the outside world and couple to G proteins on the inside of the cell. Combining molecular simulation with state-of-the-art biophysical and biochemical experiments we can know, with atomic precision, how this signal gets passed along, and the “routes” that it goes through, opening the possibility for better and newer drug development.

The liver produces bile, which the intestine uses for digestion. For the transport of bile, the liver relies on a network of microscopic tubings, known as bile canaliculi, formed by liver cells called hepatocytes. When the outflow of bile to the intestine is blocked, it collects in the liver and can lead to serious liver disease. Researchers at the Max Planck Institute of Molecular Cell Biology and Genetics (MPI-CBG) in Dresden together with experts from the Carl Gustav Carus University Hospital (UKD) and the Department for Information Services and High Performance Computing (ZIH) at TU Dresden as well as further clinics in Germany and Oslo University Hospital in Norway found that high pressure in the bile canaliculi alters the structure of

TNG-Cluster is a cosmological magnetohydrodynamical simulation of cosmic structure formation, from shortly after the Big Bang until the present day. It self-consistently solves the coupled equations of self-gravity and MHD within an expanding spacetime. It simulates several hundred galaxy clusters – the most massive gravitationally bound objects in the Universe, each with a mass of roughly 10^15 times the mass of the Sun. TNG-Cluster resolves the multi-scale interplay of astrophysics processes, from gas cooling and turbulence, to star formation, stellar evolution, supernovae explosions, to the formation of supermassive black holes and their powerful feedback energetics. It is a broad theoretical model that enables us to probe the (astro

The project studies the spectroscopic signatures of molecular clusters and ferroelectric solid solutions with extreme non-linear optical properties. It examines how atomic and electronic structure, chemical composition, and their interactions influence these signatures. Using first-principles modeling, atomistic calculations are performed within the density functional theory (DFT) framework and advanced methods like hybrid-DFT, time-dependent DFT, and many-body perturbation theory. Prototypical systems such as adamantane- or cubane-shaped clusters and crystalline solids are investigated to identify the prerequisites for optical non-linearities, guiding the synthesis of new compounds with tailored optical properties.

Within Text+, the NFDI consortium dedicated to building and providing infrastructure for the field of digital humanities, high performance computing (HPC) is gaining ground quickly. With the arrival of large language models (LLMs), the motivation for providing HPC infrastructure increased decisively. As a consequence, the first HPC service was established, easing the way for developments in several other areas where access to HPC is needed for enabling solutions otherwise not feasible. Examples of HPC use in Text+ are the Text+ LLM service and the NLP tool MONAPipe.

In this study flows over and through modelled aquatic plant canopies are investigated to better understand the interaction between the outer flow and the interior of the canopy. This is relevant for the resistance exerted by the canopy and the exchange of oxygen, pollutants, etc. between flow and canopy. Here, very detailed numerical simulations are conducted to resolve the canopy with all individual blades with an unprecedented detail. The configurations studied are densely arranged, highly flexible ribbons, which overall represent a situation very close to real seagrass meadows, much closer than in other studies. Unexpected, for example, is the observation that the blades move quite far up-wards and even further in horizontal direction.

Converging calculations is a common need in the ab initio materials-science community.
This tedious and resource-intensive process can be largely avoided if well-validated
recommendations are available. In order to create a recommender system to assist
users, benchmark data are required. This project addresses this need. It evaluates the
convergence behavior of electronic properties for a dataset of 10 materials that are
promising for optoelectronic applications.