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Fran Supek

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@FranSupek

🧬 Genetics & ML geek 🤖 PI @GenomeDataLab studying mutations, epigenet, mRNA, cancer, gene regul, AI for sci. Prof 🇩🇰 @UCPH_Research, 🇪🇸 GL @IRBBarcelona
Copenhagen/Barcelona genomedatalab.org Joined July 2009
3.3K Following 2.5K Followers 726 Posts

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Fran Supek Verified account @FranSupek
Hot off the press – new study from the group:

🧬🤖 A DNA language model for predicting mutation risk trained on massive genomic data sets

A mutation seen again and again across cancer genomes looks like a causal change. But sometimes the DNA site is simply very easy to mutate and so generates a hotspot 🔥.

We built MutFormer AI model to separate these two possibilities: operating at single-nucleotide resolution, it separates “driver” from “passenger” hotspots.

(awesome work by Ivan Galvan 🔝, Marcell Veiner @MarcellVeiner et al. 👏)
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Fran Supek Verified account @FranSupek
DNA mismatch repair (MMR) deficiency is an important driver of cancer genome instability. Yet it is usually treated as a binary label 0⃣/1⃣ MSI-high or not.

Our new preprint – fresh from the oven🔥 -- argues that this simple dichotomy obscures the underlying biology.

Trouble with different parts of the MMR machinery is "recorded" in the genome sequence as distinct mutational patterns🧬. We worked out which pattern means what.

Amazing collaborative work led by Marcel McCullough and Adam Poti, with @maiamontagnarde Maia Munteanu, at @IRBBarcelona + @UCPH_Research

Bravo, team!
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Fran Supek Verified account @FranSupek
The AI overlords have spoken! Our #NMDetectiveAI preprint (NMD genomics/deep mutational scans/mRNA language model; collab @BenLehner) seems to be in the top 1% by @qedScience 🤩

the-one-percent.qedscience.com/?selection=10.…

many congrats to 1st co-authors @IgnasiToledano & @MarcellVeiner 👏👏
QED Science Verified account @qedScience Jun 24
🎉 Meet The 1%.

QED Science evaluated 57,455 @biorxivpreprint life science preprints - blindly, at scale, and on the strength of the science itself.

Today, we’re celebrating the 574 manuscripts that rose to the top.

🏅 The 1%: the-one-percent.qedscience.com

Good science deserves to be seen.

@openrxiv @cshperspectives
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Fran Supek Verified account @FranSupek
On the heels of the release of #AlphaGenome, we have written up a review on 🧬genomic language models for DNA/RNA, out in EMBO Press @MolSystBiol:

🔖"The DNA dialect: a comprehensive guide to pretrained genomic language models" by @MarcellVeiner (nice work!👏) & yours truly👇
Kyle Tretina, Ph.D. Verified account @AllThingsApx Jan 20
The standard Transformer architecture is hitting a scaling limit in genomics. 🧱

A new review details the pivot to Hybrid Architectures (mixing Attention with SSMs like Hyena/Mamba) to efficiently model the 1Mb+ contexts vital for regulation.

But architecture isn't everything: specialized, supervised models still often outperform these massive generalist gLMs on long-range tasks.
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