Model interactions for interactive segmentation Building models through a magnifying glass.

To build a great model, one needs to take on the hat of a user. With Maximilian Rokuss, Fabian Isensee, Hallee E. Wong, and Anwesa Choudhuri we discussed how they did this for interactive segmentation.

The insights they shared are presented in this blog post: hrovatin.github.io/posts/intera...

From R to Python with minimal baggage Getting the best of both worlds.

There is no reason to stay bound to one programming language. I discussed ways to ease R-Python interoperability with Luke Zappia, Philipp Angerer, Tomasz Kalinowski.
Their tips and tricks are collected in this blog: hrovatin.github.io/posts/r_pyth...
@lazappi.bsky.social @t-kalinowski.bsky.social

Matching flows to data Models that fit like water in a vessel.

To figure out what it takes to make flow matching models solve single-cell biology questions, I discussed with Alessandro Palma, Doron Haviv, and Lazar Atanackovic.
The insights they shared are presented here: tinyurl.com/278s5m58
@dorontheviking.bsky.social @lazaratan.bsky.social

Correcting technical artifacts: The case of ambient gene expression There are many ways to crack a nut, but without the right tool none are easy.

I also published the “test post”, where I describe my battle with ambient gene expression in single-cell transcriptomic data: hrovatin.github.io/posts/ambien...

Saving time in open-source Following the trail of best practices.

For the first post, I spoke with @lukasheumos.bsky.social (scverse community) and Adrian Šošić (BayBE package) about their experiences on managing open-source packages: hrovatin.github.io/posts/open_s...

To bring to light data science topics that usually don’t make it into publications I started a blog on this topic: hrovatin.github.io By interviewing different researchers, I plan to find out what is going on in the community.

Excited to see that our effort to write down all our atlassing experience is finally published.