Stack
Computational biology and software engineering: omics analysis, sequencing technologies, programming, machine learning, databases and infrastructure.
The tools I work with, and the methods I use them for.
Computational biology
- Omics analysis
- Genomics Transcriptomics RNA biology: isoforms, polyadenylation, APA sites, modifications, splicing Phylogenetic analyses Variant calling
- Sequencing technologies
- Illumina Oxford Nanopore PacBio
Software engineering & DevOps
- Programming
- R: tidyverse, data.table, Bioconductor Python: pandas, SciPy, scikit-learn, Keras, TensorFlow/PyTorch Bash
- Machine learning
- Predictive modelling Deep learning Model development, validation and deployment for biology
- Data visualisation & reporting
- Interactive dashboards and graphics: ggplot2, shiny, plotly, rmarkdown, streamlit
- Software development
- Creator of and contributor to openly available bioinformatic tools ninetails, nanotail2, NanoQuRe, rDNAmine
- Databases
- SQL: MySQL, PostgreSQL
- Infrastructure
- Docker Kubernetes Cloud platforms: Azure
- Best practices
- Version control: Git Reproducible research