I’ve spent years writing bioinformatics tools (I’ve spent the last 6 years in industry and 90% of these tools I’ll never publish or open-source) and building infectious disease forecasting models (most of these are open-source, like FOCUS for COVID-19 [paper, code], FIPHDE for influenza [paper, code], PLANES for forecast plausibility analysis [paper, code, blog post]). Anyone who has

You upgrade your old Intel Macbook Pro for a new M4 MBP. You’re setting up a new cloud VM on AWS after migrating away from GCP. You get an account on your institution’s new HPC. You have everything just so in your development environment, and now you have to remember how to set everything up again. I just started a new position, and I’m doing this right now.

Happy Friday, colleagues. Somehow it’s September (I did not approve of this). Lots going on this week, and this is my regular attempt to close out my browser tabs I’ve accumulated over the past week with blog posts, podcasts, papers, etc. in AI, data science, genomics, public health, programming, scicomm, and other miscellany.

This week’s recap highlights biobank-scale relatedness estimation, SNP calling and haplotype phasing with long RNA-seq reads, predicting expression-altering promoter mutations with deep learning, and cross-species filtering for reducing alignment bias in comparative genomics studies.

Happy Friday, colleagues. August has flown by at warp speed. I started a new job, and my backlog of (semi-) pleasure reading grows longer. This is my regular attempt to close out my browser tabs I’ve accumulated over the past week with blog posts, podcasts, papers, etc. in AI, data science, genomics, public health, programming, scicomm, and other miscellany.

Last month I wrote about agentic coding in Positron using Positron assistant, which uses the Claude API on the back end. Yesterday OpenAI announced a series of updates to Codex, the biggest being an IDE extension to allow you to use Codex in VS Code, Cursor, Windsurf, etc. More details at developers.openai.com/codex.

I saw this Tweet a few days ago from Jeremy Leipzig counting the number of GitHub repositories that sequencing-related companies have on their organization page, but was immediately curious how many of these had an open-source license versus a restrictive or unknown license. I tried to one-shot this with GPT-5 given a screenshot of Jeremy’s Tweet and a few instructions. It got me 90% of the way but I had to make a few tweaks here and there.

Happy Friday, friends. This is my regular attempt to close out my browser tabs I’ve accumulated over the past week with blog posts, podcasts, papers, etc. in data science, genomics, public health, programming, scicomm, and other miscellany. Enjoy! Subscribe now A new study in the European Heart Journal on Accelerated vascular ageing after COVID-19 infection, and Eric Topol’s coverage on Ground Truths, COVID and our arteries.

This week’s recap highlights EviAnn for genome annotation, Vclust for viral genome clustering, MSFT-transformer for disease prediction from metagenomic data, and ConsensuSV-ONT for accurate SV calling on long-read nanopore data.

I recently reviewed a manuscript for a biotechnology journal I won’t name. The paper was clearly written by AI. I don’t mean edits or revisions here and there, I mean the entire manuscript. As if they had copied and pasted the entire contents of a certain research organization’s website into ChatGPT and asked for a paper on the topic.

I’m trying something new this week. I’ve been publishing weekly recaps on this newsletter for over a year now where I take a small deep dive into a few papers I’ve read recently. This takes time, and there’s often so much more interesting and relevant research and news in the data science + biotech space than I could possibly write about here. So I’ll be trying something different here for the next few weeks.