Deb Joye, PhD

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Deb Joye, PhD

Deb Joye, PhD

@DAMjoye

they/she | Neuroscientist & science communicator | Senior Account Supervisor @stellatecomms | I just want to tell science stories and shake things up 🧠🌈

Sacramento, CA Katılım Ağustos 2018
1.5K Takip Edilen522 Takipçiler
Deb Joye, PhD retweetledi
Arc Institute
Arc Institute@arcinstitute·
Metabolite supplementation could offer a simple, low-cost way to improve CAR T cell therapy without any changes to the cells themselves. A clinical trial in r/r DLBCL is now enrolling (NCT06610344). Paper: cell.com/cell/fulltex... Announcement: arcinstitute.org/news/ketone-su…
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Arc Institute
Arc Institute@arcinstitute·
CAR T cell therapy has shown strong results against certain cancers, but metabolic exhaustion limits its effectiveness over time. In @CellCellPress, the @MaayanLevyPhD & @ChristophThaiss labs report that a common supplement can fuel CAR T cells to fight cancer more effectively.
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Alison Preston
Alison Preston@AliPrestonPhD·
We only experience time moving forward. But memory can both predict what comes next and reconstruct what must have happened before. In a new @biorxivpreprint preprint, we show how hippocampal development enables this flexible representation of time 🧵
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Maayan Levy
Maayan Levy@MaayanLevyPhD·
β-hydroxybutyrate fuels CAR T cells better than glucose, shifting them toward a more active, less exhausted state. Supplementation improved outcomes across cancer models & boosted T cell function in healthy volunteers.
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Alison Preston
Alison Preston@AliPrestonPhD·
Every time you experience something new, your brain faces a decision: Should it update an existing memory or create a new one? In our new paper in @JNeurosci, we isolate that exact decision, moment-by-moment during learning. 🧵
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Alison Preston
Alison Preston@AliPrestonPhD·
One thing I've learned about grad student interviews is to stop asking "Why do you want to go to graduate school?" and start asking candidates to reason backward from the end of the PhD. Who will you become? What will you do that you couldn't before? You learn so much more.
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Deb Joye, PhD retweetledi
Brian Hie
Brian Hie@BrianHie·
Evo 2, our genome language model that generalizes: - across biological prediction and design tasks, - across all modalities of the central dogma, - across molecular to genome scale, and - across all domains of life, is published today in @Nature.
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Patrick Hsu
Patrick Hsu@pdhsu·
Many labs have used Evo 2 in their own work. Check out some examples below, including the first AI-generated genomes or using Evo 2 for 3D genome analysis x.com/arcinstitute/s…
Arc Institute@arcinstitute

@garykbrixi @pdhsu @MichaelPoli6 @AlisonFanton @samuelhking @GoodfireAI @AnsaBio @NVIDIAHealth @genophoria @davey_burke Since last February, Evo 2 has seen 200+ citations, 88K+ downloads, and 8M+ API requests. Groups at Yale, Johns Hopkins, NCState & UW have applied Evo 2 to problems from Alzheimer's risk prediction to 3D genome structure

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Patrick Hsu
Patrick Hsu@pdhsu·
We developed Evo Designer to help you get started with Evo right away. This tool enables DNA generation from nucleotide and species prompts. Coding region annotation is provided, with 3D protein visualization (ESMFold) for prokaryotic sequences. Sequences are scored for perplexity and per-nucleotide entropy. Check out our tutorial here: youtube.com/watch?v=6P0L1q…
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Patrick Hsu
Patrick Hsu@pdhsu·
We also release Evo 2-20B, achieving 40B-level performance on a single H100, as a drop-in replacement. See Garyk's thread below x.com/garykbrixi/sta…
Garyk Brixi@garykbrixi

To make Evo 2 more accessible, we're releasing Evo 2 20B, a checkpoint that achieves 40B-level performance on a single H100, as a drop-in replacement. This came out of model surgery with @danielchang2002, and we are excited to see people build on it! github.com/ArcInstitute/e…

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Patrick Hsu
Patrick Hsu@pdhsu·
@AlisonFanton in our lab (developer of next-gen DNA recombinases) teamed up with @aditimerch (developer of Evo semantic mining) to experimentally demonstrate cell type-specific design of chromatin accessibility. We think combining generative foundation models with task-specific predictive models is a powerful paradigm
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