#scRNA
今日のHuggingFaceトレンド

vandijklab/C2S-Scale-Gemma-2-27B
本リポジトリは、Gemma-2 27Bを基盤とし、シングルセル生物学のためにファインチューニングされた言語モデル「C2S-Scale-Gemma-27B」を提供する。
Cell2Sentence (C2S) フレームワークを用い、scRNA-seqデータを遺伝子名の配列(セルセンテンス)として処理することで、細胞種予測や組織分類などの高度な生物学的分析を可能にすることを目的とする。
vandijklab/C2S-Scale-Gemma-2-27B · Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
huggingface.co
October 21, 2025 at 10:18 AM Everybody can reply
Strong AI needs stronger data. 10x delivers the high-resolution insights to:

-Uncover hidden disease biology
-Accelerate drug development
-Lower costs (scRNA-seq at <$0.01/cell)

We partner with you from design to discovery. Achieve your AI goals. https://bit.ly/4nvHApb
October 20, 2025 at 7:00 PM Everybody can reply
Explore zebrafish heart regeneration with precision: 8 stages mapped via Stereo-seq & scRNA-seq, unlocking cardiomyocyte secrets. Impressive regeneration! PMID:40253397, Nat Commun 2025, @NatureComms https://doi.org/10.1038/s41467-025-59070-0 #Medsky #Pharmsky #RNA #ASHG #ESHG 🧪
An organ-wide spatiotemporal transcriptomic and cellular atlas of the regenerating zebrafish heart | Nature Communications
Adult zebrafish robustly regenerate injured hearts through a complex orchestration of molecular and cellular activities. However, this remarkable process, which is largely non-existent in humans, remains incompletely understood. Here, we utilize integrated spatial transcriptomics (Stereo-seq) and single-cell RNA-sequencing (scRNA-seq) to generate a spatially-resolved molecular and cellular atlas of regenerating zebrafish heart across eight stages. We characterize the cascade of cardiomyocyte cell states responsible for producing regenerated myocardium and explore a potential role for tpm4a in cardiomyocyte re-differentiation. Moreover, we uncover the activation of ifrd1 and atp6ap2 genes as a unique feature of regenerative hearts. Lastly, we reconstruct a 4D “virtual regenerating heart” comprising 569,896 cells/spots derived from 36 scRNA-seq libraries and 224 Stereo-seq slices. Our comprehensive atlas serves as a valuable resource to the cardiovascular and regeneration scientific comm
doi.org
October 20, 2025 at 6:10 AM Everybody can reply
1 reposts 2 likes
Look forward to sharing our work
@ahascience.bsky.social
#AHA25 From scRNA-seq to LLMs & AI-driven risk prediction, here’s how we’re decoding the intersection of cancer, immunity, & the heart. 💥👇 #CHIP #ICI #CardioOncology @yalecvrc.bsky.social @yalecancer.bsky.social
@Yale
October 19, 2025 at 4:57 PM Everybody can reply
1 reposts 1 likes
I've been watching $DHR. Danaher enables scRNA QC, flow and DSP to scale CAR-T/ADC. Refocus exposure: research risk narrows - buy +30% 12m analysi Track $DHR at https://bsky.app/profile/bluestocks.app/feed/stock-dhr #finsky
October 18, 2025 at 7:10 PM Everybody can reply
Benchmarking scRNA-seq copy number variation callers. #scRNAseq #CNV #Benchmarking @natcomms.nature.com 🧬 🖥️
www.nature.com/articles/s41...
October 18, 2025 at 6:05 PM Everybody can reply
1 likes
CTDP: Identifying cell types associated with disease phenotypes using scRNA-seq data #SingleCell 🧪🧬🖥️
https://www.biorxiv.org/content/10.1101/2025.10.16.682537v1
October 17, 2025 at 7:00 AM Everybody can reply
How much current foundation models for scRNA are bound to the technology used to produce data (10x or Parse)? How much to the processing pipeline?
October 17, 2025 at 6:44 AM Everybody can reply
1 likes
8/ scRNA sequencing, imaging and theory showed that large organoid monolayers exhibit a biosynthetic arrest at the center, followed by a loss of stemness and death (A pattern observed in vivo by
@batllelab.bsky.social
linkinghub.elsevier.com/retrieve/pii... )
October 16, 2025 at 9:55 PM Everybody can reply
2 likes
CTDP: Identifying cell types associated with disease phenotypes using scRNA-seq data [new]
scRNA-seq identifies disease cell types via regularized regression & permutation tests (melanoma, COVID-19, cirrhosis).
October 16, 2025 at 9:12 PM Everybody can reply
CTDP: Identifying cell types associated with disease phenotypes using scRNA-seq data https://www.biorxiv.org/content/10.1101/2025.10.16.682537v1
October 16, 2025 at 8:47 PM Everybody can reply
1 likes
CTDP: Identifying cell types associated with disease phenotypes using scRNA-seq data https://www.biorxiv.org/content/10.1101/2025.10.16.682537v1
October 16, 2025 at 8:47 PM Everybody can reply
Watching $DHR: Danaher focus on HPLC, scRNA, flow, DSP - buy +30% analysi
October 15, 2025 at 7:07 PM Everybody can reply
Monocyte differentiation dynamics and ligand-receptor interactions in peripheral blood of patients with prostate cancer and BPH: a comparative scRNA-seq analysis #SingleCell 🧪🧬🖥️
https://www.researchsquare.com/article/rs-7748159/latest
October 15, 2025 at 4:01 PM Everybody can reply
Ex-PI: Danaher = HPLC/scRNA/flow/DSP enablig mAb/CAR-T scale; Call $DHR +30% mispriced focus.
October 15, 2025 at 12:01 PM Everybody can reply
Join us next Monday for a talk by Lina Kroehling from Boston University! 🌟

🔬High-resolution Characterization of Age-specific Changes in HPV-negative HNSCC through Building a scRNA-Sequencing Atlas

⏱️ 20 October, 1 pm (AEST)
🔗 bit.ly/4hZLxiR
October 15, 2025 at 12:08 AM Everybody can reply
1 likes
As a former biotech PI: Danaher builds chromatography, scRNA, flow cytometry and DSP for mAb/CAR-T scale. Platform optionality mispriced; $DHR will rerate +30% in 12m. Refocus: depth/exposure analysi
October 14, 2025 at 5:02 PM Everybody can reply
A Comprehensive Benchmarking Study on Computational Tools for Cross-omics Label Transfer from Single-cell RNA to ATAC Data [updated]
scRNA/ATAC label transfer: Evaluates 27 tools, finds key accuracy factors.
October 14, 2025 at 6:41 AM Everybody can reply
At Osaka University, we also developed scODIN, a tool combining expert knowledge and machine learning to identify immune cell subsets in scRNA-seq data. Out now in Journal of Immunology!
github.com/jonasns/scodin
academic.oup.com/jimmunol/adv...
October 13, 2025 at 1:53 PM Everybody can reply
4 likes


Generation of synthetic scRNA-seq-like transcriptomes using a generative adversarial network from RNA-seq data

https://www.biorxiv.org/content/10.1101/2025.10.09.681449v1
October 13, 2025 at 12:33 PM Everybody can reply
I've been watching $TMO as Thermo Fisher powers Orbitrap LC-MS/MS proteomics, TMT/DIA, scRNA and DSP plus GMP cell therapy bioprocess. Market misprices platform optionality; I call +30% 12m. Analysi focus exposure
October 12, 2025 at 4:07 PM Everybody can reply
1 likes
Ex-PI: Thermo Fisher powers MS proteomics, scRNA and DSP bioprocess for cell therapy; focus/exposure shifts edge. Watch $TMO call +30% analysi opticaly
October 12, 2025 at 1:07 PM Everybody can reply
scRNA-seq identified pan-glial immunometabolism dysregulation as a central mechanism underlying electropathophysiological activity in #ParkinsonsDisease. #medsky @mainzuniversity.bsky.social

#STTT #OpenAccess: doi.org/10.1038/s413...
October 11, 2025 at 12:30 PM Everybody can reply