Robert Ahrends is Professor of Computational Mass Spectrometry at the Institute of Analytical Chemistry, Faculty of Chemistry.
He trained in biochemistry and analytical chemistry at the Justus Liebig University Giessen and already during his diploma studies focused on quantitative biology and chemical systems analysis. With an IKBPhD stipend, he expanded this analytical and chemistry-driven focus by developing quantitative proteomics strategies based onmetal-tagging and elemental mass spectrometry at the Humboldt University, Berlin.These approaches leveraged coordination chemistry and isotopic encoding for multiplexed, high-dimensional protein quantification. The resulting technologies were protected through national and international patents and established new standards for quantitative single-cell proteomics. Through this work and his time at AgilentTechnologies, he identified fundamental limitations in conventional mass spectrometry: not only in throughput and sensitivity, but in the absence of scalable computational frameworks capable of translatinghigh-dimensional mass spectrometric data into biological insight.
To address these challenges, he joined the Department of Chemical and Systems Biology at Stanford University. By integrating quantitative analytical workflows,isotope-labeled standards, and data driven computational modeling, herevealed that fat cell differentiation is anoise-dependent, multi-feedback processthat becomes irreversibly locked once acritical threshold is crossed. This workdemonstrated how computational modeling of high-dimensional mass spectrometry data can uncover nonlinear biologicaldecision processes that remain invisible topurely experimental analysis.
He subsequently established an independent research program at the Institute for Analytical Sciences in Dortmund, focusing on quantitative and computationally driven lipidomics. Since October 2023, he is Full Professor of Computational Mass Spectrometry at the University of Vienna.
Research areas
His research aims to transform mass spectrometry into a quantitative, computational platform for lipidomics and systems-levelanalysis of cellular chemistry. He and his team established Lipidomics Informatics for Life Sciences (LIFS), a computational infrastructure that systematically maps lipid chemical space and enables scalable interpretation of large-scale lipidomics datasets. The group develops integrated analytical and computational strategies tostudy lipid–lipid interactions, enzymatic lipid remodeling, and the dynamic role of lipids in membrane organization andsignaling. The long-term goal is to establish quantitative, computation-enabled chemical frameworks that make complex cellular communication measurable and predictive,and to identify novel molecular targets fortherapeutic intervention, particularly incardiometabolic disorders. “Our research aims to quantitatively decode the complex relation of lipids and translate this chemical space into newstrategies for understanding and treatinglipid-related diseases”.
More infos:
ahrendslab.univie.ac.at/news/news-details/news/inaugural-lecture-robert-ahrends/
