wilco 🌐
1.9K posts

wilco 🌐
@willabe_13
grad school @Tufts Kaplan lab. Postdoc @uottawa Pelling Lab. Interests in Neuro, BME, Tiss Eng. Working on something w @brilliantlabs.

Ok this figure is pretty intimidating...

The next wealth pump -- if we let it gizmodo.com/americans-reco…




If you ever want to be a founder, the best thing you will do in your 20's is to save money and visit SF. Let nobody convince you that any other ecosystem in the world comes close. It doesnt. But you wont believe it until you see it for your self and truly experince it. I didnt either.




Locking participation in biology behind 10+ year apprenticeships means we don’t get child prodigies like you can get in math and physics. Reducing the amount of tacit knowledge required to *participate* in biology could unlock “genius” sooner




A shocking number of synthetic biologists got into it because of jurassic park.




This is really cool (and wild): Scientists simulated a complete living cell for the first time. Every molecule, every reaction, from DNA replication to cell division. The paper (Luthey-Schulten et al., Cell 2026, doi.org/10.1016/j.cell…), just out today, used JCVI-Syn3A — a synthetic minimal bacterium with fewer than 500 genes. A 3D+time simulation of the full 105-minute cell cycle: DNA replication, protein translation, metabolism, division. Every gene, protein, RNA, and chemical reaction tracked through physical space. It took years to build. Multiple GPUs. Six days of compute time per run. And this is the simplest possible cell. A human cell has ~20,000 genes. It lives in tissue. It interacts with neighbors. It differentiates. It responds to drugs in ways that depend on context we haven't fully measured. Mechanistic simulation of the minimal cell costs 6 GPU-days for 105 minutes of biology. You cannot scale that to human cells. The complexity isn't 40x harder. It's exponentially harder. This is why the field pivoted to data-driven models. You can't hand-encode the regulatory wiring of a human hepatocyte. But you can learn it — if you have the right perturbation data collected across enough diverse biological contexts. The two approaches aren't competing. Papers like this generate the ground truth that future ML models need for validation. But the path to a clinically useful virtual cell runs through foundation models, not through scaling up mechanistic simulation. Amazing work!






