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Paulina Nuñez-Valencia

@paulinanunezv.bsky.social
273 followers 828 following 1 posts

PhD student - Machine Learning for Conservation. Dias&Frazer Lab @crg.eu with Mafalda Días and @jonnyfrazer.bsky.social

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Reposted by Paulina Nuñez-Valencia
Ezequiel Galpern @eag91.bsky.social · 25/09/2026
🧬 What do deep-learning models for proteins actually learn? Our new review looks at how model predictions relate to fitness, folding stability and function. With @cwjpugh.bsky.social, Mafalda Dias & @jonnyfrazer.bsky.social 🔗 chemrxiv.org/doi/full/10....
chemrxiv.org
From sequences and structures to fitness, folding and function: challenges in the age of AI | ChemRxiv
Deep-learning models have transformed our ability to predict the phenotypic effects of sequence perturbations. Protein language models (pLMs) score the evolutionary propensity of any amino-acid substi...
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Reposted by Paulina Nuñez-Valencia
Ezequiel Galpern @eag91.bsky.social · 08/08/2026
🚨 Paid MSc research opportunity at CRG Barcelona! With Mafalda Dias and @jonnyfrazer.bsky.social, we’re hosting a 4-month MSc project: 🧬 “Folding versus function: disentangling the molecular mechanisms of missense variants in gene-trait associations” More info 👇 www.crg.eu/en/content/t...
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Reposted by Paulina Nuñez-Valencia
Ezequiel Galpern @eag91.bsky.social · 05/08/2026
1/ New preprint! with @solersanchisx.bsky.social @cwjpugh.bsky.social @federicobilleci.bsky.social @jonnyfrazer.bsky.social and Mafalda Dias, we introduce a scalable framework to improve stability prediction and separate folding from functional constraints. www.biorxiv.org/content/10.6...
biorxiv.org
Blending physics-based and inverse folding models to disentangle variant effects on stability and function
Protein sequences are constrained not only by the need to fold into stable structures, but also by specific functional requirements imposed by natural selection. Yet predictions of how amino-acid chan...
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Reposted by Paulina Nuñez-Valencia
Jonathan Frazer @jonnyfrazer.bsky.social · 23/10/2025
Applications are open for the @crg_eu PhD Programme! 20 fully funded positions — including one in our group through the Evolutionary Medical Genomics ITN. Join us to develop deep generative models of cross-species data to tackle open questions in disease genetics. www.crg.eu/en/content/t...
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Paulina Nuñez-Valencia @paulinanunezv.bsky.social · 26/05/2025
Check out our new preprint! How can we get more out of existing protein/genome language models without retraining them?
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Reposted by Paulina Nuñez-Valencia
Anshul Kundaje @anshulkundaje.bsky.social · 26/05/2025
Awesome paper. Simple post-hoc trick (averaging over homologs) with elegant evolution theory dramatically improves zero shot coding variant effect prediction in pLMs & actually delivers better results from the larger models (inverting the trend with raw likelihoods). 1/
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Isabelle Zane @isabellease.bsky.social · 22/05/2025
@cwjpugh.bsky.social at #VariantEffect25
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Reposted by Paulina Nuñez-Valencia
Jonathan Frazer @jonnyfrazer.bsky.social · 22/05/2025
Proud supervisor moment! Next up at #VariantEffect25: Charles Pugh @cwjpugh.bsky.social, PhD student in Mafalda’s and my group, presents: From Likelihood to Fitness: Improving Variant Effect Prediction in Protein and Genome Language Models #AI #ProteinML
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Reposted by Paulina Nuñez-Valencia
Jonathan Frazer @jonnyfrazer.bsky.social · 21/05/2025
A lovely summary of what we have learnt about scaling from ProteinGym -- Have we reached a performance plateau? More on this later in the week from @cwjpugh.bsky.social
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