Seva Viliuga

@proteinator.bsky.social

PhD candidate in bioinformatics Protein structure prediction / Protein design

New pre-print from PhD student Hang Zou on warm-starting the variational quantum eigensolver using flows: Flow-VQE! Flow-VQE is parameter transfer on steroids: it learns how to solve a family of related problems, dramatically reducing the aggregate compute cost!

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My lab, at Karolinska, in Stockholm, is looking for a PhD student with a computational/quantitative background to work on probabilistic/generative models of proteins (structure and sequence). The research will involve methods development, and applications in vaccine design.

While this paper looks interesting, let me just say (again) that (essentially all) NMR ensembles in the PDB are NOT thermodynamic ensembles or meant to represent these. They are "uncertainty ensembles" and using them to benchmark machine learning (or other) models of dynamics is not a good idea.

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bioRxivpreprint@biorxivpreprint.bsky.social · 2y ago

Towards Unraveling Biomolecular Conformational Landscapes with a Generative Foundation Model https://www.biorxiv.org/content/10.1101/2025.05.01.651643v1

Small proteins can be more complex than they look! We know proteins fluctuate between different conformations- but by how much? How does it vary from protein to protein? Can highly stable domains have low stability segments? @ajrferrari.bsky.social experimentally tested >5,000 domains to find out!

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