Bioinformatician working at the intersection of computational biology, single-cell omics, and genome mining.
I work on biological data analysis, genome mining, sequence analysis, and reproducible bioinformatics workflows.
My experience includes:
- single-cell RNA-seq and scATAC-seq analysis
- genome mining for ribosomally synthesized and post-translationally modified peptides
- protein and nucleotide sequence analysis
- clustering, taxonomy, and phylogenetic analysis
- workflow development in Python and R
- scientific visualization and reporting
- Developing a bioinformatic pipeline to identify and prioritize prenylated RiPP candidates
- Integrating sequence similarity, taxonomy, clustering, and phylogeny
- Building reproducible and automated analysis workflows
- Expanding expertise in single-cell omics and scientific software development
Programming: Python, R, SQL, C++, Bash/Shell
Bioinformatics: NGS data analysis, single-cell RNA-seq, scATAC-seq, genome mining, sequence analysis, functional annotation, phylogenetics, taxonomy analysis, Seurat, ArchR, Biopython, BLAST, DIAMOND, MAFFT, IQ-TREE
Data Analysis & Visualization: pandas, NumPy, ggplot2, matplotlib, scikit-learn, statistics, Power BI, Tableau
Machine Learning & AI: machine learning fundamentals, scikit-learn, AlphaFold, AI-assisted scientific analysis
Workflow & Development Tools: Git, Linux, Conda, Nextflow, VS Code, Jupyter, Streamlit