
bioengineer | @try_litefold
conserved motif
Joined April 2025
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did some simulations on a wide range of targets a while back and this pretty much holds true
Replying to @RolandDunbrack
My current mental model of ipSAE is that the low end (depends on the target) is extremely predictive of nonbinding, but higher values are not. So it is useful but not perfect at filtering. Per @amirshanehsaz's comment, 11/60 ain't bad!
nabajit (bio/acc) retweeted
As said before, if we are going to do agentic science, lets do it in a right, controlled way, just like how controlled reproducible experiments looks like.
All u gotta do is just connect ur lab.
Ahem ahem. Topic: Own and Customize everything
294 Connectors across target science, mol engineering, developmental biology. DBs, tools, atlases, just ask for it. You can add custom ones.
200+ skills along the same lines. Add custom skills.
Give permissions to all the platform workflows.
Add custom instructions, give permissions what your agents can and can not use and when to ping you. Even create your own subagents.
Compute: Select the compute capacity you need when agentic coding requires gpus.
We have found ways where we have ontologically organized every connector and skill, use jev-like decision models, and cut the token cost by half, and actually getting better accuracy in using the right things in the right time.
As said before, if we are going to do agentic science, lets do it in a right, controlled way, just like how controlled reproducible experiments looks like.
nabajit (bio/acc) retweeted
Glycosylation is among the most important modifications in biology.
We know relatively little about glycobiology, because it is hard to study.
This Nat Rev Methods primer describes our best tools for analyzing glycosylation 🔽
Everything about this is terrible
Excited to announce WARHOUND. techcrunch.com/2026/10/22/be…
this is so cool
how do the 100 blockbuster drugs actually work?
I mapped every one onto its 3D target structure and explained how they work. Small molecules to ADCs.
atlas.dominikscherm.de
Hill climbing biology is coming
I asked Google CEO Pichai what happened to the missing Gemini 3.5 Pro model that never shipped.
He gave me an interesting window into the hard decisions big labs have to make in model development:
"While training the 3.5 series, we had Flash and Pro, which we were working on. An area we internalized through the middle of this year was that there were gaps in agentic capabilities, particularly around coding...
We wanted to definitely hill climb there, and the team felt the fastest way to do so was using Flash. It's a smaller model and more efficient, so you can really get a lot more iterative loops there. That's what led to 3.5, 3.6, 3.7, and 3.8 Flash.
By the time we got that done, we had a chance to apply it to Pro, but Argon pre-training was done."
nabajit (bio/acc) retweeted
PhD teaches you time is cheap and money is expensive.
Startup teaches you the inverse.





















