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cemselb/README.md

Hello, I'm Cemsel ๐Ÿ‘‹

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

Currently leading computational strategies to develop non-invasive diagnostics for endometriosis at endogene.bio.


๐Ÿงฌ 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.

๐Ÿ› ๏ธ Core Technical Skills

๐Ÿ’ป Programming & Scripting R Linux Bash Perl LaTeX Python

โ˜๏ธ Workflow & Infrastructure AWS HPC Conda Nextflow Docker Git

๐Ÿ”ฌ Bioinformatics & Multi-Omics Bulk & scRNA-seq Whole Genome Methylation GWAS Polygenic Risk Scores (PRS) In Silico Drug Screening Biomarker Discovery Patient Stratification

๐Ÿ“ˆ Analytics & Machine Learning Machine Learning Models Drug Efficacy Prediction Regression Analysis Dimensionality Reduction (PCA/UMAP) Time-to-Event Modeling


๐Ÿ”ฌ Key Research Highlights

๐Ÿฉธ 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.

๐ŸŽ—๏ธ 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).

๐Ÿ“š Selected Publications

  • Tiniakou et al., 2026: Whole genome methylation profiling of menstrual stem cells identifies novel biomarkers for endometriosis (Commun Med).
  • Pรฉrez-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).

๐Ÿ‘‰ View my full publication list here

Google Scholar ORCID Zenodo


๐Ÿ“Š GitHub Stats

Cemsel's GitHub Stats

Cemsel's Top Languages


๐Ÿ“ซ Connect with Me

Bluesky LinkedIn

๐Ÿ“ Munich, Germany

๐Ÿ’ฌ Native Cypriot Turkish | English (C2) | German (B1)

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  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