New Journal Paper about Computational identification of protein complexes from network interactions: Present state, challenges, and the way forward
Sara published a review paper in a collaboration with Zoran Nikoloski from the Max Planck Institute of Molecular Plant Physiology and the Intitute of Biochemistry and Biology at the University of Potsdam about the “Computational identification of protein complexes from network interactions: Present state, challenges, and the way forward”
New Journal Paper about Genetic Characterization of Rat Hepatic Stellate Cell Line HSC-T6 for In Vitro Cell Line Authentication
In a great collaboration with Prof. Weiskirchen from the RWTH University Hospital Aachen we published a new paper about the “Genetic Characterization of Rat Hepatic Stellate Cell Line HSC-T6 for In Vitro Cell Line Authentication”
Nikita gave a talk at the 8th HEFagrar PhD Symposium from the Hans Eisenmann-Forum in Freising about “Deep Learning-based Early Weed Segmentation using UAV Images of Sorghum Fields”.
Josef joins the team as research assistant. He will work on novel machine learning methods for time series forecasting within the project “Digital management support systems for small and medium-sized enterprises in value chains of ornamental plants, perennials and cut flowers (PlantGrid)”, funded by the Federal Office of Food and Agriculture.
Recently, the student council of the TUM Campus Straubing (TUMCS) for Biotechnology and Sustainability awarded the prize for excellent teaching for the first time to Prof. Dr. Dominik Grimm. A “Tree of Teaching” behind the new “Sustainable Chemistry” teaching and research building facing the Danube is dedicated to him. The student council had already chosen Prof. Grimm as the winner last year, and now the students congratulated him with a sign next to a newly planted silver willow after completion of the new building and the adjacent green space.
We published an original research paper on a comparative study with several Machine Learning and classical forecasting algorithms to predict horticultural sales.
Jonathan joins the team as PhD students. He will work on novel machine learning and reinforcement learning problems within the project “Reinforcement Learning for Automated Flowsheet Synthesis of Steady-State Processes”, funded by the German Research Foundation (DFG).
Together with Computomics GmbH we successfully attracted funding from the Federal Ministry of Education and Research (BMBF) for our new project “CropML: New machine learning techniques for more accurate plant breeding by integrating heterogeneous external factors”.
We published a novel machine learning algorithm EVARS-GPR an EVent-triggered Augmented Refitting of Gaussian Process Regression for Seasonal Data. Florian presented the method at the German AI Conference. The talk can be found on youtube: https://youtu.be/jZ6hZNMa-TE