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project is to develop a high-performance computing framework for mass spectrometry proteomics to enhance efficient processing and interpretation of large datasets using deep learning algorithms and GPU
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developed by the project partners will be based on two key technologies: machine learning algorithms that generate artificial yet realistic data points (synthetic health data) and secure multi-party
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particle (SEP) events. The project is a joint collaboration of Algorithmics and Computational Intelligence research group at the Department of Computing and Space Research Laboratory at the Department
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