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models of protein structures and complexes for application in life sciences. In addition, we develop and maintain PLINDER, a resource designed to drive breakthroughs in deep learning-based protein-ligand
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of Bioinformatics, we develop SWISS-MODEL (https://swissmodel.expasy.org ), a widely used web-based platform for generating high-accuracy 3D models of protein structures and complexes for application in life sciences
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of Bioinformatics, we develop SWISS-MODEL (https://swissmodel.expasy.org ), a widely used web-based platform for generating high-accuracy 3D models of protein structures and complexes for application in life sciences
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systemic perspective enables us to study new technologies and their interdependencies at the level of the circular economy itself. The module will provide integrated frameworks and tools based on advanced
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, forest structure, lidar and topography data, into deep learning (e.g., Transformers and CNNs) algorithms. Analyze the importance of environmental variables on the deep learning model accuracy. Establish
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100%, Zurich, fixed-term The modeling of nano-scale devices such as field-effect transistors or memory cells consists of predicting and optimizing the performance of not-yet fabricated components