Aditi Merchant

BioE PhD student @stanford in the Hie Lab // ML for SynBio

[Aditi Merchant @aditimerch]

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 with desired functions.🧵

https://t.co/P5qVJB3qIY

[Aditi Merchant @aditimerch]

Evo 2 is out! Huge congrats to @garykbrixi and the rest of the team, was a blast working on some of the design tasks! The future of genome language models looks bright!

[Garyk Brixi @garykbrixi]

Evo 2 is out in Nature today, showing that genome language models can predict and design across the full complexity of life, from phages to eukaryotes.

A few surprises from the project, including how ignoring trillions of nucleotides was key to getting a good model. 🧵

[nature @Nature]

Nature research paper: Semantic design of functional de novo genes from a genomic language model

https://t.co/vB53a2eIGM

[Ars Technica @arstechnica]

Generative AI meets the genome https://t.co/rSs1uCx9BS

[Samuel King @samuelhking]

Semantic design, our method leveraging contextual relationships between genes for function-guided biological sequence design, is now out in @Nature!

This work was led fearlessly by @aditimerch, who inspires all of us in the lab every day. She carried out this immense project with mind-blowing speed, while graciously supporting numerous other projects and being a genuinely brilliant and kind presence.

Please read more about the work in her thread below!👇

[Arc Institute @arcinstitute]

Published today in @Nature, @aditimerch & researchers from the @BrianHie lab report that the large-scale genomic model, Evo, is capable of using surrounding genomic context to produce novel, functional genes, enabling an emergent approach they've termed 'semantic design'.

[Brian Hie @BrianHie]

Today in @Nature, in work led by @aditimerch, we report the ability to prompt Evo to generate functional de novo genes.

You shall know a gene by the company it keeps! 1/n

[David Li @_David_Li]

Check out this amazing work by the incredible @aditimerch and team!! Prompting DNA language models a la guilt-by-association lets you design things that function with low seq id

[Garyk Brixi @garykbrixi]

Context can steer Evo to generate multi-gene interactions (toxins and anti-toxins, anti-CRISPRs) that function in the lab.
Many of the functional sequences have very low sequence similarity to any natural gene. Read the thread and paper

Congratulations @aditimerch!

[Aditi Merchant @aditimerch]

This was all possible because of the support of my incredible PI @BrianHie and my amazing labmates @samuelhking and @exnx. I’m forever grateful to be surrounded by people who inspire me to be a better scientist.

To learn more, check out the paper: https://t.co/P5qVJB3qIY

[Aditi Merchant @aditimerch]

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 with desired functions.🧵

https://t.co/P5qVJB3qIY

[Aditi Merchant @aditimerch]

Together, this work suggests that genomic sequence models can meaningfully generalize beyond characterized natural evolution. Looking forward, we hope that semantic design can serve as a starting point for function-guided design and optimization of genes across biology.

[Aditi Merchant @aditimerch]

De novo antibody design with experimental success rates that require testing only tens of candidates! Such an inspiring success from the incredibly hardworking Germinal team— huge congrats!

[Santiago Mille @santimillef]

The ability to design antibodies against any protein of interest has major implications for medicine, biotech, and basic science.

Today, we introduce Germinal, a pipeline for epitope-targeted de novo antibody design achieving  4–22% success rates with efficient experimental validation.