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Odysseas Vavourakis

@odyv.bsky.social
550 followers 765 following 17 posts

Generative Antibody Design at Oxford | ovavourakis.github.io | 🇬🇧🇩🇪🇬🇷(🇪🇸) he/him

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Reposted by Odysseas Vavourakis
Jeffery Pendleton @jefferypendleton.bsky.social · 13/08/2026
A future does not have to be probable to matter. Our new paper asks how uncertain climate futures become cognitively and institutionally usable for decision-making, bringing together constructive memory, Mental Time Travel, scenario planning and deep uncertainty. www.frontiersin.org/journals/cog...
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Odysseas Vavourakis @odyv.bsky.social · 15/06/2026
Today, we're announcing SAbDab2! In brief: - clean, pre-processed antibody structure data for ML with standardised train/test splits - massive improvements in structure organisation and annotation consistency - support for VNARs and antibody construct annotation - more structures than ever before
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Reposted by Odysseas Vavourakis
Mohammed AlQuraishi @moalquraishi.bsky.social · 13/03/2026
New OpenFold3 preview out! (OF3p2) It closes the gap to AlphaFold3 for most modalities. Most critically, we're releasing everything, including training sets & configs, making OF3p2 the only current AF3-based model that is functionally trainable & reproducible from scratch🧵1/9
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Reposted by Odysseas Vavourakis
Jeffery Pendleton @jefferypendleton.bsky.social · 22/01/2026
I’m excited to share my first peer-reviewed publication, and my first first-author paper, "Time in mind: a multidisciplinary review on temporal perception, cognition, and memory" is now published open access in Frontiers in Cognition! www.frontiersin.org/journals/cog... #psychology #science #time
frontiersin.org
Frontiers | Time in mind: a multidisciplinary review on temporal perception, cognition, and memory
This review examines temporal cognition through the lens of Mental Time Travel (MTT): the subjective experience of recalling past events and using them to co...
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Reposted by Odysseas Vavourakis
Fabian Spoendlin @fspoendlin.bsky.social · 20/03/2025
Predicting protein conformational flexibility remains a major challenge in structural biology. While we can now accurately model static protein structures, understanding their dynamics is still difficult, largely due to a lack of suitable training data.
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Odysseas Vavourakis @odyv.bsky.social · 27/01/2025
It’s an exciting time in protein design! 🧬✨ But much of the therapeutic potential—especially for antibodies—remains untapped. Why? 🤔 Antibodies seem like ideal candidates for design! 💉 Here’s a quick thread summarising our new review paper on the state of antibody structure prediction. 👇 1/
sciencedirect.com
Challenges and compromises: Predicting unbound antibody structures with deep learning
Therapeutic antibodies are manufactured, stored and administered in the free state; this makes understanding the unbound form key to designing and imp…
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