Genetic epidemiology for cancer risk, prognosis, and prevention.

I study inherited genetic susceptibility to cancer and complex traits, bringing together genome-wide association studies, bioinformatics, and large-scale epidemiologic data to ask practical questions about risk and clinical outcomes.

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My work sits at the intersection of cancer epidemiology, human genetics, machine learning, and computational biology.

I am a genetic epidemiologist and doctoral researcher dedicated to uncovering the mechanisms behind cancer, complex traits, and drug responses. I am pursuing a Ph.D. in Genomic Epidemiology at DKFZ and Heidelberg University, with an academic background in Molecular Biology and Genetics.

Across my research path, I have worked on genetic variants associated with complex human diseases, genome-wide association studies of cancer susceptibility, lymphoid neoplasm classification, pancreatic cancer risk, and earlier molecular evolution and systematics projects in insects.

I am currently working on combining electronic health records (EHR) and genetic data to understand cancer risk, prognosis, and how inherited variation can inform epidemiologic and clinical questions.

Education

Advanced training in genomic epidemiology, biology, and genetics.

Ph.D.

Genomic Epidemiology
Heidelberg University & German Cancer Research Center (DKFZ)
2021 – 2026

M.Sc.

Biology
Cumhuriyet University
2012 – 2015

B.Sc.

Molecular Biology and Genetics
Cumhuriyet University
2007 – 2011

Scientific Memberships

  • InterLymph Consortium2021 – present
  • AVE Alliance2022 – present
  • IGES2022 – present
  • EHA2021 – present

Grants & Fellowships

  • Monika Kutzner Stiftung – Project Grant (GENIE-GEN)2025
  • Republic of Türkiye Ministry of National EducationPhD Scholarship, 2021–2025
  • InterLymph Consortium – Travel Grant2023, 2026
  • European School of Haematology (ESH) – Scholarship FundTravel Grant, 2022

Projects and resources

Tools, tutorials, and resources I maintain or contribute to.

CanCode

A standardized cancer phenotype framework for reproducible cohort design in biobanks.

Open CanCode

i-CLASSi

A standardized lymphoid neoplasm classification framework, integrating InterLymph hierarchy, vocabulary mappings.

Open i-CLASSi

GWAS Tutorial

A practical tutorial for genome-wide association study workflows in cancer research.

Open Tutorial

GWAS Studies

Genome-wide association studies and genetic research projects.

Lymphoid Neoplasm (PhenoCluster)

Phenotype: Lymphoid neoplasms
GWAS Catalog: GCST90624736–GCST90624750
Publication GitHub Zenodo

Pancreatic Cancer (Frozen GWAS)

Phenotype: Pancreatic cancer
GWAS Catalog: Available after review
GitHub Zenodo

Get in Touch

Feel free to reach out for collaborations, research inquiries, or general questions.

Email: murat.guler@dkfz.de

Location: Heidelberg, Germany

Connect: LinkedIn • GitHub • Twitter • Scholar

“If we knew what it was we were doing, it would not be called research, would it?” Albert Einstein
“We cannot teach people anything; we can only help them discover it within themselves.” Galileo Galilei
“Those among us who are unwilling to expose their ideas to the hazard of refutation do not take part in the scientific game.” Karl R. Popper, The Logic of Scientific Discovery