Tweets about spatial biology including genomics, transcriptomics, proteomics, or other -omics in general. Some tweets about single-cell DNA or RNA sequencing.
Congrats to @ZhuBokai and the wonderful team! Ever feeling frustrated with annotating cells from a spatial-omics dataset with a small targeted panel? CellSNAP helps by leveraging info from cell location and tissue image via a parallel GNN architecture.
biorxiv.org/content/10.1101/…
Excited to share our AI research on brain tumor classification from H&E images, now published in @NatureMedicine! 🎉
Honored to be a co-first author with @danhtai_hoang. This work was co-led by @NCIEytanRuppin and @NCIKenAldape.
Check out our tweetorial:
#AI#DigitalPathology
Our new study is now out in @NatureMedicine! We introduce DEPLOY, a deep-learning model that enhances the diagnosis of CNS tumor subtypes. DEPLOY predicts methylation profiles from H&E slide images for classification. #CancerResearch#AI#DeepLearningshorturl.at/gjCOR 1/n
#BGI-Research's cutting-edge liver studies have been selected as the cover story for @NatureGenet . These two studies integrate scRNA-seq and Stereo-seq data to characterize molecular signatures and interactions of liver cell types across different states including homeostasis, damage, repair, and regeneration. bit.ly/3vKGd0D
Spatial Transition Tensor or STT, developed by Qing Nie and colleagues @UCI_CMCF is a method that connects messenger RNA splicing and cell state transitions across spatiotemporal dimensions.
nature.com/articles/s41592-0…
We've begun rolling out anatomical annotations to the Allen Brain Cell Atlas!
The first data set to support these annotations is the MERFISH Spatial Transcriptomics Dataset of a Single Adult Mouse Brain - registered to CCFv3. 🔗 knowledge.brain-map.org/abca…
Wanna annotate cells in your spatial-omics data but tired of just calling them by their general phenotypes? Hey we got the solution for you! See awesome thread by the hotshot @ZhuBokai, and working with maestros @ZongmingMa and @GarryPNolan
SpiDe-Sr
Spatial proteomic images denoising & super-resolution
#SpatialProteomics
⏫peak signal-to-noise ratio & cell extraction accuracy in #ImagingMassCytometry
"In denoising module training, a pair of sub-sampled images (g1(y), g2(y)) were generated from noise image y with the sub-sampler G......as the input and target to train the denoising network (Uθ)"
Also applicable to immunofluorescent images
vs SRCNN KernelGAN RCAN
@NatureComms 2024
nature.com/articles/s41467-0…
Is cell segmentation a solved problem? Maybe not yet, but the results of this multimodality cell segmentation challenge get us closer! (Spoiler, the winner is a generalist Transformer-based model). @BoWang87nature.com/articles/s41592-0…
Thrilled to announce our paper in @Nature introducing MUSIC! For the first time, MUSIC enables simultaneous mapping of multiplexed chromatin interactions, RNA-chromatin interactions, RNA-RNA interactions & gene transcription at single-cell resolution. doi.org/10.1038/s41586-024-0…
DART-FISH
#SpatialTranscriptomics
Pad-lock probe
Rolony
RiboSoma for cell segmentation
Detect <1kb short RNA (able to probe pri-microRNAs?😁)
Very nice reading if interested in how to design/optimize imaging-based ST methods👍
121 genes for human Cortex
300 genes for human kidney (Look at the exquisite closely-apposed single-cell-resolved glomerular Endothelial-Mesangial-Podocyte niche!😍)
@KunZhangBioE@NatureComms 2024
nature.com/articles/s41467-0…