Cemal Erdem

SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) Fellow

Multi-omics data integration, machine learning, and large-scale mechanistic modelling

Kontakt

Verksam som

Biträdande universitetslektor vid Institutionen för medicinsk biovetenskap

By 6M, Sjukhusområdet Umeå universitet, 901 85 Umeå

The overall theme of the Erdem Lab is to merge machine learning and mechanistic models with patient data to create clinically predictive computational models for cancer and other diseases.

Research Interests

Mathematical modeling of signaling cascades
Systems biology
Quantitative Systems Pharmacology (QSP)
Precision medicine

Links

Bacterial stress responses lower mRNA–protein level correlations

Proceedings of the National Academy of Sciences of the United States of America, Proceedings of the National Academy of Sciences (PNAS) 2026, Vol. 123, (38)

Süer, Sena G.; Arnoux, Jérôme; Lim, Yi Y.; et al.

Liquid biomarkers associate with TGF-β Type I receptor and hypoxia in kidney cancer

Signal Transduction and Targeted Therapy, Springer Nature 2025, Vol. 10, (1)

Mallikarjuna, Pramod; Erdem, Cemal; Ilundain Beorlegui, Ruben; et al.

Mechanistic modeling of cell viability assays with in silico lineage tracing

PloS Computational Biology, Public Library of Science (PLoS) 2025, Vol. 21, (8)

Mutsuddy, Arnab; Huggins, Jonah R.; Amrit, Aurore K.; et al.

Mechanistic modeling of cell viability assays with in silico lineage tracing

Mutsuddy, Arnab; Huggins, Jonah R.; Amrit, Aurore; et al.

Computational speed-up of large-scale, single-cell model simulations via a fully integrated SBML-based format

Bioinformatics Advances, Oxford University Press 2023, Vol. 3, (1)

Mutsuddy, Arnab; Erdem, Cemal; Huggins, Jonah R; et al.