Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

How cool is this? Michal Lipinski from Broad Institute presenting stacked #Illumina spatial slides of the mouse brain with subcellular transcriptome resolution #AGBTGM

76,643 görüntüleme • 1 yıl önce •via X (Twitter)

7 Yorum

Martin Smith profil fotoğrafı
Martin Smith1 yıl önce

Visualized with Celldega:

ksminnovation profil fotoğrafı
ksminnovation1 yıl önce

Dr. Tal Patalon explores how AI mega initiatives like the $500B Stargate project & AI-powered genomic analysis by Illumina & NVIDIA are transforming healthcare. @TalPatalon @forbes @edengallery_ #AIinHealthcare #PrecisionMedicine #Multiomics #HealthTech

Shayan Mohammadmoradi, MS, PhD profil fotoğrafı
Shayan Mohammadmoradi, MS, PhD1 yıl önce

@broadinstitute very cool!

TrolliProf profil fotoğrafı
TrolliProf1 yıl önce

@broadinstitute Really cool

Ayub Khattak profil fotoğrafı
Ayub Khattak1 yıl önce

@broadinstitute Amazing

TeslaElon SpaceXFan profil fotoğrafı
TeslaElon SpaceXFan1 yıl önce

@broadinstitute 😮

@cornhundred on bluesky profil fotoğrafı
@cornhundred on bluesky1 yıl önce

@broadinstitute Thanks for sharing!! Follow our team @

Benzer Videolar

🚀 Introducing scGPT-spatial! 🧬🌍 A game-changing spatial-omic foundation model, built on the powerful scGPT framework with MoE (mixture of experts) and continually pretrained on a massive 30 million spatial single-cell profiles! 🧠 What’s the challenge? Spatial transcriptomics is next-level complex—not only must we model single-cell/spot profiles, but we also need to capture intricate spatial relationships while handling diverse sequencing protocols (imaging-based vs. sequencing-based). 🔥 Why scGPT-spatial? ✨ A Spatial-omic Foundation Model with Continual Pretraining – Built on scGPT’s robust initialization, it unlocks spatial context in tissues. ✨ SpatialHuman30M Dataset – The largest curated dataset: 30M profiles from Visium, Visium HD, Xenium, and MERFISH across 821 slides. ✨ Revolutionary MoE Decoders – A cutting-edge Mixture of Experts (MoE) architecture for protocol-aware gene expression decoding. ✨ Spatially-Aware Training Strategy – A neighborhood-based masked reconstruction approach to capture complex cell-type colocalization. ✨ Multi-Modal & Multi-Slide Integration – Seamless clustering & spatial domain identification across slides and modalities. ✨ Cell-Type Deconvolution & Gene Imputation – Unlocks cross-resolution & cross-modality harmonization with fine-tuned embeddings. 📄 Read the preprint: 💻 Explore the code/weights: #SpatialTranscriptomics #SingleCell #AIResearch #MachineLearning #SpatialData Huge shoutout to the incredible PHD students Chloe (ChloeXWang) and Haotian (Haotian Cui) for leading this groundbreaking project! 🎉 Massive thanks to our amazing co-authors Andrew, Ronald, and Hani (Hani Goodarzi) from Arc Institute—this work wouldn't have been possible without you! 👏

Bo Wang

59,066 görüntüleme • 1 yıl önce