Billy Palmer

271 posts

Billy Palmer

Billy Palmer

@BillyHPalmer

Immunogenomics at Regeneron

Tarrytown, NY Katılım Mart 2018
234 Takip Edilen231 Takipçiler
Billy Palmer retweetledi
Fergal Waldron
Fergal Waldron@FergalWaldron·
🔥🚨@TargetALS funded TDP-43 RNA aptamer preprint🚨🔥 Using deeply phenotyped #ALS post-mortem tissue cohorts we show nuclear TDP-43 pathology is an early event, co-incident with STMN-2 cryptic splicing, preceding cytoplasmic aggreg. & symptom onset 🧵1/4 biorxiv.org/content/10.110…
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Nancy Zhang
Nancy Zhang@NancyZh60672287·
What gets erased when you integrate #singlecell data across samples/studies, and can you get it back? When samples are from e.g. healthy & disease, should you simply massage cells together? FINALLY, I feel we can answer this question: doi.org/10.1101/2023.0…
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Science Immunology
Science Immunology@SciImmunology·
A mass screening of immune activating receptors on natural killer cells shows how different peptide variants can affect innate immunity. @mjwsim @NIAIDNews Check out the study: scim.ag/43l
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Bo Wang
Bo Wang@BoWang87·
🎉Exciting Update of scGPT 🎉: After receiving significant attention from the community since our April release, we're thrilled to announce the first major update for scGPT - a foundation model for single-cell multi-omic data. This update integrates community feedback and leverages the latest data release from @cellxgene. It boasts larger pretraining data, and more robust models, and expands the range of application tasks. Pre-print (V2) available: biorxiv.org/content/10.110… Access our open-source code and models here: github.com/bowang-lab/scG… Detailed tutorials: scgpt.readthedocs.io/en/latest/ Highlights of this update include: 🔬 Introducing the first GPT-style foundation model for single-cell multi-omic data, pretrained on over 33M human cell atlas data. 💡 Our generalist approach enables one model to accomplish multiple tasks in single-cell analysis, including multi-omic integrative analysis and perturbation prediction. 🧬 Discovering gene-gene interactions specific to various conditions using learned attention weights and gene embeddings. 🚀 Uncovered a scaling law showcasing continuous model performance enhancement as data volume increases. 🐾 scGPT model zoo (see github) now offers multiple pre-trained foundation models for various solid organs and a comprehensive pan-cancer model. Begin exploring your data with the most fitting foundation model. We welcome your thoughts on specialist vs generalist approaches in single-cell studies. Many thanks for the following technical analyses of scGPT: 1. Excellent twittorial by @simocristea: x.com/simocristea/st… 2. Comprehensive review on LLM in cell biology by @s_batzoglou: towardsdatascience.com/large-language… 3. Insightful blog by @SalvatoreRaieli: levelup.gitconnected.com/scgpt-when-tra… Kudos to Haotian (@HAOTIANCUI1) & Chloe (@chloexwang1) for their exemplary work on this project. @VectorInst @pmcc_ai @UHNAIHUB @bradwouters @drbarryrubin @UofT_TCAIREM @UofT_LMP @UofTCompSci @uoftmedicine
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Billy Palmer
Billy Palmer@BillyHPalmer·
Such a fun project to work on with contributions from so many. Special shout out to Norman lab members who worked on this @laleaton @anaacodo Liyen Loh @PN0rmski
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Billy Palmer
Billy Palmer@BillyHPalmer·
HHLA2 has already garnered interest as a therapeutic target. Our results suggest that KIR3DL3 is an interesting candidate for immune checkpoint blockade due to its tissue-specificity, its association with a unique set of TCRs, and its role as an inhibitory receptor.
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