Ruben Props

This paper quantifies single-cell phenotypic diversity in microbial communities using Raman spectroscopy and the Hill diversity framework to study stress-induced changes.

This paper compares flow cytometry and Raman spectroscopy for analyzing bacterial phenotypic heterogeneity, showing flow cytometry's population-level resolution and Raman's single-cell biochemical detail.

The paper uses machine learning to link bacterial taxa with heterotrophic production in freshwater lakes using flow cytometry and 16S rRNA data.