RAND corp AIxBio report, AI accelerating: GPT-4b for stem cell reprogramming; AI is slowing down; UVA SDS on Bluesky; LLMs and education; Python needs R's CRAN;

Developing an R package using the OpenAI Codex agent in Positron

Using R and the GitHub API to get licensing information for GitHub repos for sequencing-related companies, one-shot with GPT-5.

Best AI for R, the weight of a cell, R+MCP, AI is a mass delusion event, AI hiring freezes, Quarto+Positron, biology moonshots, Julia for R users, AI hallucination, nf-core advisories...

Genome annotation, viral genome clustering, metagenomic diagnostics, SV analysis on ONT reads, functional prediction, gene loss, DNA damage/repair, CRISPR metagenomics, LLM lit review, ...

ChatGPT can be (mis)used to conduct scientific peer review with a predetermined outcome.

Closing my browser tabs: papers, blogs, news stories, YouTube videos, tutorials, etc.

This week’s recap highlights analysis of human de novo mutation rates from a four-generation pedigree reference, how LLMs internalize scientific literature and citation practices, the py_ped_sim forward pedigree and genetic simulator for complex family pedigree analysis, and a review on predicting gene expression from DNA sequence using deep learning models like Enformer and Borzoi.

I recently wrote a piece about leaving academia for biotech. I left academia for industry in 2019. I spent four years at a consulting firm before joining Colossal Biosciences. This week I’m returning to the University of Virginia School of Data Science as a tenured associate professor and dean of research. The transition from academia to industry can be tricky, but it’s also increasingly common.

This week’s recap highlights nanoMDBG for metagenome assembly from nanopore reads, the SCassist AI-based workflow for single-cell analysis, discovery and characterization of GxE and GxG effects in a vertebrate model, the PIGEON framework for estimating gene-environment interaction for polygenic traits, and long-read alignment with multi-level parallelism.

I’ve written a lot about Ollama here. Ollama lets you run open-weight models like Llama, Gemma, Mistral, Qwen, DeepSeek, etc. on your own computer. You don’t have to pay for a frontier model like ChatGPT, Claude, or Gemini, and all the inputs and outputs stay on your computer, minimizing any privacy and security concerns. Until recently Ollama was a command-line only tool.