Hi there 👋

I am Michael Kaufman PhD, a Senior Research Scientist at the University of Colorado Anschutz Medical Campus.

My programming superpowers are:
Python :snake: | R :chart_with_upwards_trend: | Rust :crab: | Bash :shell:

I work as an Bioinformatics Analyst for the CU Cancer Center in the Bioinformatics and Biostatistics Shared Resource (BBSR), specializing in single-cell RNA-seq analysis and spatial transcriptomics. Previously I was an Informatics Fellow with the RNA Biosciences Initiative (RBI) on campus.

How can bioinformatics help us understand cancer?
Single-cell RNA-seq and spatial transcriptomics, in particular, have revolutionized cancer research by revealing the cellular and molecular complexity of tumors at high resolution. scRNA-seq uncovers tumor heterogeneity, identifies rare cell populations, and characterizes the tumor microenvironment. Spatial transcriptomics adds tissue context, mapping gene expression to physical locations and uncovering cell–cell interactions. Together, they provide a comprehensive view of tumor biology, aiding in biomarker discovery and precision therapy. My goal is to leverage these technologies to advance our understanding of cancer biology and hopefully inspire new treatments through data-driven insights.

My favorite bioinformatics tools are:
Rstudio :factory: | VS Code :computer: | GitHub :octocat: | Nextflow :test_tube: | Snakemake :snake: | Docker :whale: | Conda :package: | Bioconductor :dna: | HPC :cloud: | Seurat :bar_chart: | Cell Ranger :test_tube: | Space Ranger :city_sunrise:

I have particular interest in using GitHub for:

• single-cell RNA-seq analysis and visualization
• developing computational methods for spatial transcriptomics
• writing and maintaining reproducible pipelines and analysis workflows
• coding bioinformatics CLI tools and libraries in Python, R, and Rust
• contributing to open-source bioinformatics software
• learning how to further apply machine learning and AI to bioinformatics and cancer research