Yanay Rosen
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yanayrosen.bsky.social
Yanay Rosen
@yanayrosen.bsky.social
CS PhD Student at Stanford. Machine Learning + CompBio
Website: http://yanay.ai
Reposted by Yanay Rosen
Out today in @naturegenet.bsky.social -- PERFF-seq! With @tsionabay.bsky.social , @ronanchaligne.bsky.social, Bob Stickels, Meril Takizawa, + Ansu Satpathy, we describe this new assay to study rare populations with programmable nucleic acid cytometry. 1/n
www.nature.com/articles/s41...
Transcript-specific enrichment enables profiling of rare cell states via single-cell RNA sequencing - Nature Genetics
Programmable Enrichment via RNA FlowFISH by sequencing (PERFF-seq) isolates rare cells based on RNA marker transcripts for single-cell RNA sequencing profiling of complex tissues, with applicability t...
www.nature.com
January 8, 2025 at 1:30 PM
Very excited to see our perspective on Building the AI Virtual Cell published today in Cell! 🏗️🔮⭐️ www.cell.com/cell/fulltex...

With @bunnech.bsky.social @yusufroohani.bsky.social, Jure Leskovec, Emma Lundberg, Stephen Quake, Aviv Regev and Theofanis Karaletsos
How to build the virtual cell with artificial intelligence: Priorities and opportunities
Advances in AI and omics enable the creation of AI virtual cells (AIVCs)—multi-scale, multimodal neural network models that simulate molecules, cells, and tissues across diverse states. This vision outlines their design and collaborative development, promising to transform biological research through high-fidelity simulations, accelerating discoveries, and fostering interdisciplinary open science collaborations.
www.cell.com
December 12, 2024 at 7:53 PM
Reposted by Yanay Rosen
🧬 Thrilled to share Knowledge Graph GWAS (KGWAS), the largest AI model that integrates >10 millions of multi-modal and multi-scale functional genomics data to improve GWAS power by 100% while discovering novel disease-critical variants, genes, cells, and networks!

1/15🧵
December 9, 2024 at 5:42 PM
Reposted by Yanay Rosen
1/🧬 Excited to share PLAID, our new approach for co-generating sequence and all-atom protein structures by sampling from the latent space of ESMFold. This requires only sequences during training, which unlocks more data and annotations:

bit.ly/plaid-proteins
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December 6, 2024 at 5:44 PM
Reposted by Yanay Rosen
Introducing ESM Cambrian, a new family of protein language models, focused on creating representations of the underlying biology of proteins.
December 4, 2024 at 5:45 PM