I bridge clinical microbiology leadership with computational genomics, specializing in antimicrobial resistance (AMR) prediction and scalable diagnostic workflows. With 10+ years in clinical diagnostics and an MSc in Bioinformatics from the University of Birmingham, I understand both the wet-lab constraints and computational complexity of modern genomic analysis.
- AMR Prediction: Developing interpretable ML models for antimicrobial resistance using genomic data
- Pipeline Engineering: Building reproducible, production-grade workflows with Nextflow and Snakemake
- Clinical Authority: Translating lab diagnostics into scalable bioinformatics solutions
- Genomic Analysis: WGS, variant calling, clinical interpretation, and ML-driven diagnostics
- Languages: Python (Pandas, Scikit-learn), R (Tidyverse, Bioconductor), Bash/Linux
- Bioinformatics: Nextflow, nf-core, Snakemake, WGS, RNA-Seq, Variant Calling, Assembly
- ML/DL: XGBoost, LightGBM, PyTorch, SHAP, DNABERT
- Infrastructure: AWS (EC2, S3), Docker, Git, SQL, HPC
- Lab Expertise: Clinical Microbiology, AST, AMR, Diagnostic Workflows, Lab Management
- kleb-amr-project: Interpretable deep-learning and ensemble models for predicting multidrug resistance in Klebsiella pneumoniae (MSc Dissertation, University of Birmingham)
- 20-stage Snakemake workflow with temporal validation
- XGBoost, LightGBM, CNN, and DNABERT-2 comparison
- SHAP-based interpretability analysis
- Thesis: github.com/NasirNesirli/kleb-amr-project
- MSc Bioinformatics - University of Birmingham (2025)
- 10+ years clinical leadership - Clinical Microbiology, Lab Management, Diagnostic Implementation
- Clinical Authority: Understanding AST methodologies, EUCAST/CLSI standards, real-world sample variability
Advancing clinical genomics through remote collaboration within the European biotech & clinical ecosystem. Eligible for EU Blue Card.
- Website: nasirnesirli.com
- GitHub: github.com/NasirNesirli
- LinkedIn: linkedin.com/in/nasirnesirli
- Email: [email protected]
- ORCID: 0009-0005-3038-7781