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Cemal Erdem Lab

Research group Our lab works on integrating multi-omics datasets, machine learning, and large-scale mechanistic models to build clinically predictive computational models.

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


Google Scholar

Head of research

Cemal Erdem
Assistant professor


Participating departments and units at Umeå University

Department of Medical Biosciences
Jian-Feng Mao and Cemal Erdem sit across from each other at a white table and discuss.
Cemal Erdem and Elin Chorell seek collaborators at a Lunch Pitch

The pitches covered cancer and disease modeling and the role of sphingolipids in metabolic diseases.

Latest update: 2024-03-01