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this is most of all true for the actual trainees. protecting them can inadvertently block them from opportunities they want. don't be that guy

overall, way fewer people are arguing against our policy as change seems inevitable now

A few quick bullets: protecting trainees from career risk is a common argument

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It will certainly be important to include more modalities (and scientists) beyond X-ray, which we hope to do in the future! Lots of fun work to be done to ensure interoperability in that way

Haha I love that, thanks for actually clicking the link 😂

Oops fixed! Also here seemay.substack.com/p/from-syste...

More on our reflections here seemay.substack.com/p/from-syste...

Doing this will require co-iterating across an entire data system, not just refining one part. And we're experimenting with how to share all of this (our real-time thinking, pivots, tools, data) openly and quickly all outside of traditional journals

Tldr, we're focusing on diffuse scattering, which is the messier background signal in X-ray diffraction images. These data are often tossed because they're complex, but this complexity is where so much of the interesting biology sits

Our take: more of the same data won't get us there. We're bringing together top experts across almost every node of the X-ray pipeline to generate the right kind of data to model ensembles of different protein conformations. Think: pictures to movies

We're dreaming about the next frontier in structural biology: protein motion. Understanding how proteins move will be the next big unlock for predicting function

Most importantly, first in our new series of organismal spotlight shorts (open source illustrations coming soon!). Sea squirts! www.youtube.com/watch?v=-E9T...

Wrote up a post summarizing some of our big picture lessons on bottlenecks, such as difficulties in finding tacit "folklore" knowledge in organismal systems arcadiascience.substack.com/p/zoogle-sug...

Hoped others would jump on it, but wasn't super straightforward so we ran with some predictions ourselves. Ultimately collaborating with sea squirt and choano experts to scope some pilots (biggest filter was finding people willing to publish openly/rapidly but we prevailed!)

We recently released the Zoogle dataset, which uses our workflows and publicly avail data to quantify how well different organisms model specific human genes/diseases. zoogle.arcadiascience.com/about

Props to those taking the first steps. Those first steps are scary, messy, and the only guarantees I can offer is that now we have a chance at something better. More announcements in coming months.