Stefan Enroth

Natural Sciences Fellow, SCAS.
Associate Professor of Computational Genomics, Uppsala University

As an undergraduate, Stefan Enroth studied engineering with a specialization in information tech-
nology at Uppsala University and École Normale Supérieure de Lyon. After working in the industry,
focusing on machine learning in wearable computers, he came back to academia and defended his
PhD in Bioinformatics in the Disciplinary Domain of Science and Technology, Uppsala University,
in 2010. He was promoted to Associate Professor (Docent) of Computational Genomics in the Di-
sciplinary Domain of Medicine and Pharmacy, Uppsala University, in 2014.

Enroth’s current research aims at characterizing and understanding factors that influence the abun-
dance of human proteins and using this knowledge to develop personalized models for biomarker
discovery in non-communicable diseases, especially gynecological cancers, and for prediction of
individual characteristics from plasma protein profiles. He also investigates the possibilities and limi-
tations of sampling methods such as self-collected, dried blood spots in relation to protein biomarkers.

Enroth has published extensively on high-throughput analysis of DNA, RNA and protein data in relation
to human health and disease. His current publication list includes over 80 articles with more than 12,000
citations in total. Notable recent works include the first scientific use of the proximity extension assay in
a large cohort (Enroth et al., Nature Communications, 2014), comparisons of proteomics in self-collected,
dried blood spots vs. assisted phlebotomy (Broberg et al., BioEssays, 2021) and development of an 11-
protein biomarker risk score for ovarian cancer (Enroth et al., Communications Biology, 2019).

At SCAS, Enroth will work on developing multivariate prediction models of ovarian cancer from high-
throughput proteomics using self-collected, dried samples of cervico-vaginal fluid. 

This information is accurate as of the academic year 2021-22.