Advancing and Assessing Modelling and Analysis Methods in the Context of Systems Biomedicine
Due to the rapid progress in developing experimental techniques, establishing and improving analysis methods is one of the major challenges in computational life sciences. For many analysis tasks, however, the limitations and performance of competing methods remain unknown, and there are no clear rules or guidelines for selecting the optimal analysis method. Benchmark studies have proven to be valuable tools for evaluating the performance and applicability of analysis approaches. However, they are often subject to methodological limitations and deficiencies, leading to potential bias in the results. In my presentation, I will give an overview of novel approaches developed in my group in the context of mathematical modeling and omics analyses. In particular, I will summarize our ongoing efforts to improve the methodology of benchmark studies. By generally incorporating rigorous planning, design, and analysis principles in benchmark studies, we aim to promote the development of novel analysis approaches and the identification of
decision rules for optimal method selection in practice. Especially in view of the enormous efforts to apply deep learning methods in all areas of research, reliable performance comparisons are of great importance.
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