Bioinformatics Data Analyst specializing in the intersection of computational biology and data science. I analyze complex high-throughput transcriptomic data alongside wet-lab results (or vice versa?).
Programming stack:
- Main language is
Python- Core Data Analysis libraries such as
pandas,numpy,scikit-learn,scipy - Core Visualisation libraries such as
matplotlib,seaborn,plotly&pycirclize,upsetplot(you may have heard of the latter two?) - Specific RNA-seq analysis libraries such as
gseapy,pydeseq2(and others I am certainly forgetting)
- Core Data Analysis libraries such as
R- I use it just enough to remember why I prefer PythonbashSQL
Currently, I am deepening my focus on software engineering. I am also actively exploring the application of large language models (LLMs) and retrieval-augmented generation (RAG).
These repositories contain my own work, without any LLM-generated code. I promise the irony of using an LLM to help write a README about avoiding LLMs is not lost on me.
P.S. Redo of Healer the best anime ever. Change my mind