What I write

My best writings are in theoretical biology. I take concepts that are easily mixed up and I separate them.

• My Tracer-seq discussion separates clonal trees from lineage trees.
• My critique of Perturb-ATAC separates genetic interactions from statistical interactions.

What I read

• Maciej Ceglowski on scurvy and internet ads.

• Scholars Stage for an American perspective on China and its neighbors.

• Donat Studios for software engineering tidbits, especially this raucous post about CSV’s.

• Jake VanderPlas on Python for data science, especially this excellent conda myth debunker.

• The Online Etymology Dictionary by Douglas Harper.

• Gwern Branwen’s amazing monthly reading lists on AI and human genetics. He also writes about all sorts of things such as why are girl scout cookie prices outpacing inflation? He follows problems with superhuman persistence.

• Slate Star Codex contains diverse, fascinating essays, but what hooked me at first was the cost disease post.

• CodingHorror on programming effectively and Julia Evans on being delighted to do it.

• John Cook on math, stats, and programming.

• On statistics StackExchange, I greatly admire user whuber. Check out his stunning highlighting of the infamous Broad Street pump. I also admire the post from user ttnphs on visualizing CCA.

• If you’re interested in the history of science, grab a copy of Edward Tufte’s “Visual Explanations: Images and Quantities, Evidence and Narrative”. Read the fabulous chapters on the Challenger disaster and the Broad Street cholera outbreak.

• Random Critical Analysis on health policy.

• GrokInFullness on the opioid epidemic.

• The Incidental Economist and the Medical Care blog on healthcare.

• Will Kimball on trombone history.

• Stephen M. Hendrick on disease ecology

• Ben Thompson on tech companies.

• This hilarious preprint on arguments against the possibility of artificial general intelligence.