Rate My Professor Stein Aerts

Aerts' research specializes in regulatory genomics, gene regulatory networks, single-cell omics technologies, machine learning in genomics, Drosophila neuroscience, and cancer regulatory heterogeneity. His laboratory develops bioinformatics methods such as SCENIC for single-cell regulatory network inference, cisTopic for cis-regulatory topic modeling on single-cell ATAC-seq data, pySCENIC, CREsted for modeling cell-type-specific enhancers, and SCENIC+ for multiomic inference of enhancers and networks. Key publications include "Cell-type-directed design of synthetic enhancers" (Nature, 2024), "SCENIC+: single-cell multiomic inference of enhancers and gene regulatory networks" (Nature Methods, 2023), "Fly Cell Atlas: A single-nucleus transcriptomic atlas of the adult fruit fly" (eLife, 2021), "Cross-species analysis of enhancer logic using deep learning" (Nature Biotechnology, 2020), "A scalable SCENIC workflow for single-cell gene regulatory network analysis" (Genome Biology, 2020), and "SCENIC: single-cell regulatory network inference and clustering" (Nature Methods, 2017). He co-founded the Fly Cell Atlas consortium. Aerts has earned major honors including an ERC Advanced Grant for Genome2Cells (2022), Methusalem Grant for BioMedAI (2026), EMBO membership (2022), ERC Consolidator Grant (2017), Prize for Bioinformatics and Computational Science from the Biotech Fund (2017), AstraZeneca Foundation Award for Bioinformatics (2016), FWO Postdoctoral Fellowships (2005 and 2008), and HFSP Young Investigator Grant (2010). He serves on the board of the KU Leuven Center for Human Genetics and Genomics Core and is a member of Leuven.AI, LISCO - KU Leuven Institute for Single Cell Omics, KU Leuven Brain Institute, and KU Leuven Cancer Institute.