A reproducible, cloud-scale reanalysis of five peer-reviewed studies on cellular aging, reprogramming, and rejuvenation, and an honest account of what survived contact with a shared pipeline.
A Python CLI tool that strips background noise from any video file using ML denoisers — while copying the video stream byte-for-byte. A 6 GB 4K file processes in minutes instead of hours.
Single-cell RNA sequencing is one of those techniques that generates a huge amount of data and then demands a huge amount of effort to interpret it. You run the sequencer, get a matrix of 20,000 genes by several thousand cells, and then spend the next several days (or weeks) figuring out what’s in there. I… Read More: I Built a Single-Cell RNA-seq Pipeline That Writes Its Own… »
A small, cracker-themed block puzzle I cloned and polished for my four-year-old — built in plain vanilla JavaScript with synthesised audio, a Three.js bloom backdrop, and a deliberately forgiving combo system. Free to play, open source on GitHub.
I rebuilt two published CHO cell-culture papers — a hybrid ODE + machine-learning growth model, and a genome-scale metabolic reduction pipeline — as an interactive digital twin that runs in the browser. Here’s how it works, what’s under the hood, and an honest take on what it’s good for. No hosted version yet; the code is on GitHub and a live instance is coming soon.
The Gap Between Models and Tools I’ve seen a lot of impressive ML models in biopharma that never get used. Not because the science is wrong, but because the tool doesn’t fit into anyone’s workflow. The model might be published in Nature Methods with beautiful receiver operating characteristic curves, but if a discovery scientist can’t… Read More: Building ML Tools Scientists Will Actually Use »