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Bayesian optimization (BO) has become an established framework and popular tool for hyperparameter optimization (HPO) of machine learning (ML) algorithms. While known for its sample-efficiency, vanilla BO can not utilize readily available prior beliefs the practitioner has on the potential location of the optimum. Thus, BO disregards a valuable source of information, reducing its appeal to ML prac
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This topic of this thesis is how the presence of biomembrane molecules affect the behavior of a protein related to Parkinson’s disease in a simplified (compared to in the cell) model system.Lipids are fat molecules that make up the biological barriers in our body that control transport of essential molecules in and out of the cell and create an environment where membrane proteins can perform their
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The focus of this doctoral dissertation was to develop novel and scalable computational genomics methods for analysing single-cell genomic modalities. Scarf, a highly memory-efficient single-cell data analysis toolkit, was developed to enable an analysis of very large-scale datasets on personal computers, and the execution of parallel workflows on server-scale computational systems. The advances i
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Background: Obesity is a risk factor for endometrial cancer but whether metabolic dysfunction is associated with endometrial cancer independent of body size is not known. Methods: The association of metabolically defined body size phenotypes with endometrial cancer risk was investigated in a nested case–control study (817 cases/ 817 controls) within the European Prospective Investigation into Canc