Pim Huis in 't Veld

@huis.bsky.social

Chromosome biology and genome stability | @vienabiocenter, University of Vienna, Austria | https://www.maxperutzlabs.ac.at/research/research-groups/huis

I'm surprised a community of publishing writers can blame AI for the problems of peer review when those same writers cite our study, "the strain on scientific publishing", which characterizes how this problem existed before AI. bit.ly/StrainQSS It's the incentives structure, not the AI. 1/n

Ask the Chefs: Peer Review Capacity — Uncomfortable Truths and Overlooked Conversations - The Scholarly Kitchen

For Peer Review Week 2026, we asked the Chefs two questions: What is one uncomfortable truth about peer review that the scholarly publishing community doesn’t talk about enough? And, beyond recruiting...

scholarlykitchen.sspnet.org

We are recruiting a postdoctoral fellow to study DNA damage repair via the homologous recombination pathway using quantitative cell biology approaches. The position will be initially supported for two years by the MSU Research Foundation Postdoctoral Scholars program. Please share! 1/5

🧵 Short thread: I give a seminar to 1st-year biomed PhD students in my program about how to critically read a paper, how to extract VAST amounts of information from the title, and why reading AI summaries instead of struggling with papers is *particularly* bad for trainees. 🧪

A comparative analysis of two paper titles, focusing what exactly we can expect to see in each paper. The verb choice alone shows that one is primarily a techniques paper.

They hate immigrants doing farm work and construction, and they hate immigrants working in research labs. They hate immigrants speaking languages they can't understand, and they hate immigrants speaking perfect English. Their little White Nationalist worldview just can't handle it.

So (if I understand this correctly), the way AI (companies) will "solve" all the major problems in maths, biology, and medicine in the next 5 years will be by stealing and building on the ideas of researchers naive enough to think their chats with AI companies would be private.

I'd like to be in cat. 3, but the 1% cut-off locks me in cat. 2.. For me it defeats all possible positive aspects in a dominant negative manner. AI to browse claims across papers would be great. But please avoid quality scores and cut-offs. For one because they focus on words >> data+figure quality

Richard Sever@richardsever.bsky.social · 4mo ago

I suspect reactions will fall into 3 categories: 1) excitement ‘because AI’; 2) revulsion; 3) questions whether this may be the beginning of more multi-dimensional approaches to ranking papers without reading them (which many want) 1/2

Reposting this from April 1, 2007 in honor of Craig Venter. I did this as an April Fool's joke - sharing it as a PDF. I got stressed when I found out Craig had seen it and knew it was by me. But he loved it and said it was OK to share it more widely. So then I posted it on the web.

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Excited to share our discovery of a new programmable RNA-guided DNA-targeting system hiding inside bacteriophages that predates CRISPR. We call it VIPR (Viral Interference Programmable Repeat), and it uses an entirely new logic to find its targets. Thread + link below.

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Since our preprint on the ETC-ATP synthase supercomplex has attracted attention, I would like to introduce the platform we used, Langtaosha. It was launched by SMART together with several other institutions with support from Open Life Science Alliance, aiming for long-term open infrastructure 1/4

Alexey Amunts@amunts.bsky.social · 6mo ago

65 years after Peter Mitchell’s chemiosmotic theory, we report an association between ATP synthase and the electron transport chain. In the preprint led by @longzhou88.bsky.social, we describe a large supercomplex and show how the supramolecular organization contribute to oxidative phosphorylation 🧵

ROCKET 🚀 inference-time optimization of AlphaFold to fit structural data is published! rdcu.be/fa9YH Since our preprint, we’ve pushed it to regimes where other methods break: low resolution, weak signal, real experimental edge cases. Here’s what we learned: 1/15

AlphaFold as a prior: experimental structure determination conditioned on a pretrained neural network

Nature Methods - ROCKET improves experimental structure elucidation by integrating implicit structural knowledge from OpenFold, a trainable reimplementation of AlphaFold2, with X-ray...

rdcu.be