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cemselb/README.md

Hello, I'm Cemsel 👋

Senior Bioinformatics Scientist | Multi-omics & Biomarker Discovery | Precision Medicine

Currently leading computational strategies to develop non-invasive diagnostics for endometriosis at EndoGene.Bio.


🧬 About Me

  • Current Focus: Developing clinically-relevant diagnostic models using whole genome methylation and transcriptomics data.
  • Expertise: Specialist in patient stratification and disease progression prediction using large-scale genomic datasets.
  • Background: PhD in Cancer Sciences from The University of Manchester with a focus on genomic risk prediction.
  • Research History: Previous roles at Klinikum rechts der Isar (TUM), Wellcome Trust Sanger Institute, and the University of Oxford.

🛠️ Core Technical Skills

💻 Programming & Scripting R Linux Bash Perl LaTeX Python

☁️ Workflow & Infrastructure AWS HPC Conda Nextflow Docker Git

🔬 Bioinformatics & Multi-Omics Bulk & scRNA-seq Whole Genome Methylation GWAS Polygenic Risk Scores (PRS) In Silico Drug Screening Biomarker Discovery Patient Stratification

📈 Analytics & Machine Learning Machine Learning Models Drug Efficacy Prediction Regression Analysis Dimensionality Reduction (PCA/UMAP) Time-to-Event Modeling


🔬 Key Research Highlights

🩸 Endometriosis & Reproductive Health

  • EndoGene.Bio: Leading the development of a novel, non-invasive diagnostic for endometriosis.
  • Sanger Institute: Validated single-cell transcriptomics of menstrual fluid as a source for non-invasive diagnosis of endometrial pathologies.
  • Oxford/Bayer Partnership: Identified and validated drug targets and biomarkers for endometriosis.

🎗️ Oncology & Neurology

  • Endometrial Cancer: Developed and validated a novel PRS using Manchester, UK Biobank and ECAC data.
  • Neurological Disorders: Performed GWAS and meta-analyses for multiple sclerosis using large-scale biobank data (IMSGC, MultipleMS).

📚 Selected Publications

  • Tiniakou et al., 2026: Whole genome methylation profiling of menstrual stem cells identifies novel biomarkers for endometriosis (Commun Med).
  • Pérez-Moraga et al., 2025: Beyond one-size-fits-all: single-cell transcriptomic signatures predict drug efficacy and reveal responder subgroups in endometriosis (bioRxiv).
  • Bafligil et al., 2022: Development and evaluation of polygenic risk scores for prediction of endometrial cancer risk in European women (Genet Med).
  • Tapmeier et al., 2021: Neuropeptide S receptor 1 is a nonhormonal treatment target in endometriosis (Sci Transl Med).

👉 View my full publication list here

Google Scholar ORCID Zenodo


📊 GitHub Stats

Cemsel's GitHub Stats

Cemsel's Top Languages


📫 Connect with Me

Bluesky LinkedIn

📍 Munich, Germany

💬 Native Cypriot Turkish | English (C2) | German (B1)

Pinned Loading

  1. nf-singlecell-biomarker nf-singlecell-biomarker Public

    A Nextflow pipeline for scRNA-seq quality control, filtering, and dimensionality reduction.

    Python

  2. gwas gwas Public template

    A scalable pipeline for GWAS quality control, imputation processing, and survival analysis.

    R

  3. nf-emseq nf-emseq Public

    Reproducible Nextflow pipeline for EMseq data processing and methylation analysis.

    Shell