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Aditi Merchant

@adititm.bsky.social
330 followers 567 following 25 posts

BioE PhD student @ Stanford in the Hie Lab // ML for Synthetic Biology

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Reposted by Aditi Merchant
Nature @nature.com · 25/11/2025
Nature research paper: Semantic design of functional de novo genes from a genomic language model go.nature.com/48uEnAn
go.nature.com
Semantic design of functional de novo genes from a genomic language model - Nature
By learning a semantics of gene function based on genomic context, the genomic language model Evo autocompletes DNA prompts to generate novel genes encoding protein and RNA molecules with defined activities, whose sequences generalize beyond those found in nature.
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Reposted by Aditi Merchant
Brian Hie @brianhie.bsky.social · 19/11/2025
Today in @nature.com, in work led by @adititm.bsky.social, we report the ability to prompt Evo to generate functional de novo genes. You shall know a gene by the company it keeps!
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Reposted by Aditi Merchant
Arc Institute @arcinstitute.org · 19/11/2025
Published today in @nature.com, @adititm.bsky.social & researchers from the @brianhie.bsky.social lab report that the large-scale genomic model, Evo, is capable of using surrounding genomic context to produce novel, functional genes, enabling an an emergent approach they've termed 'semantic design'.
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Aditi Merchant @adititm.bsky.social · 19/11/2025
What if we could autocomplete DNA based on function? Today in @Nature, we share semantic design—a strategy for function-guided design with genomic language models that leverages genomic context to create de novo genes and systems with desired functions. 🧵 www.nature.com/articles/s41...
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Reposted by Aditi Merchant
Di Jiang @dijiang319.bsky.social · 22/12/2024
New @biorxiv-synthbio.bsky.social on #Evo 👀⤵️🧵 introducing Evo 1.5 for semantic mining + SynGenome - an AI-generated genomics database #AI #synbio #LLM🧬 @adititm.bsky.social @brianhie.bsky.social et al. @arcinstitute.org
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Aditi Merchant @adititm.bsky.social · 19/12/2024
Excited to have the first project of my PhD out!! By leveraging genomic language model Evo’s ability to learn relationships across genes (i.e., "know a gene by the company it keeps"), we show that we can use prompt-engineering to generate highly divergent proteins with retained functionality. 🧵1/N
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