The research group of Dr. Röst uses computational approaches to understand clinical phenomena on a personalized level and study biological phenomena from a systems perspective. He develops experimental and computational approaches for mass spectrometry (MS) that drive improved identification and quantification of small molecules and peptide analytes. He specifically focuses on next-generation mass spectrometry approaches using a combination of high mass resolution and fast scan speeds MS to comprehensively acquire information about a biological specimen. In particular, he has developed methods and software for data-independent acquisition (DIA) mass spectrometry, most notably the OpenSWATH and TRIC software which allow automated analysis of SWATH mass spectrometry data. The software is developed as open source and the Rost lab is one of the core developers of the OpenMS C++ framework. In his lab, he combines robust software engineering with advanced signal processing and machine learning methods to extract information from highly multiplexed MS data (specifically DIA data). Dr. Röst applies these methods to acquire comprehensive data about protein or small molecule analytes in complex biological samples such as whole cell lysates or tissue samples. In his lab, he studies cellular systems to gain deeper insight into the exact molecular causes of disease and the genotype to phenotype relationship. Secondly, he uses proteomics and metabolomics approaches in a personalized medicine context to study human subjects in a longitudinal fashion throughout disease progression, specific perturbations and medical interventions. Ultimately, his lab is interested in systematically profiling human specimens in health and disease to gain deeper insight into molecular causes of disease. The SWATH-MS method that he co-developed has been widely adopted in the field and now multiple other MS vendors (Thermo Fisher, Waters, Bruker) are offering the method on their instruments. Dr. Röst is a frequent invited speaker at major international conferences in the field (Dagstuhl (Germany), ASMS (US), HUPO (international), EuBIC (international), US-HUPO (US) and CNPN (Canada)). For his work, Dr. Röst has received the 2018 US HUPO “Gilbert S. Omenn Computational Proteomics Award” for achievements in computational proteomics.