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.