@CJM_lab Profile picture

Jinmiao Chen Lab

@CJM_lab

Chen Jinmiao Lab for single cell Immunology and AI

Joined April 2023
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Jinmiao Chen Lab Reposted

🚀 scEnrichment Update! The scEnrichment tool now features an updated reference geneset with 524 cell type 🧬 and phenotype 🔬-related genesets! 🎯 Input your geneset to uncover enriched phenotypes or cell types with ease. 🔗 Try it here immunesinglecell.org/tool/sc_enrich… #scRNAseq

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Jinmiao Chen Lab Reposted

Rediscovering publicly available single-cell data with the DISCO platform academic.oup.com/nar/article/do…


Jinmiao Chen Lab Reposted

🚀 Exciting update! DISCO now supports batch downloads—access data from 113,277,088 cells across 18,402 samples with ease. Perfect for training your LLMs or fueling other applications! 🌐📊 #SingleCellData #Bioinformatics #AI @LLM immunesinglecell.org/download

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Jinmiao Chen Lab Reposted

Our data showed varied functions of myeloid cells in early life while identifying therapeutic targets. We are grateful to our collaborators @FGinhoux @HongyanWang9 @lai9uan @CJM_lab @Abhay_R_ and their teams for all their support, ideas, tools, and enthusiasm over the years!

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Jinmiao Chen Lab Reposted

Exiting new method, looking forward to trying it!

Very excited to present STAMP: An Interpretable spatially aware dimension reduction of spatial transcriptomics nature.com/articles/s4159…



Jinmiao Chen Lab Reposted

Congratulations to our bioinformatics collaborator @CJM_lab for yet another excellent method to decipher the #spatialtranscriptomics data. I look forward to the future of deeper understanding of #tumourmicroenvironment with our powerful partner!

Very excited to present STAMP: An Interpretable spatially aware dimension reduction of spatial transcriptomics nature.com/articles/s4159…



Jinmiao Chen Lab Reposted

Some of you may know I have been handling lots of spatial omics lately. Very excited for this new way of thinking of SRT dimension reduction for improved analysis.

Very excited to present STAMP: An Interpretable spatially aware dimension reduction of spatial transcriptomics nature.com/articles/s4159…



Jinmiao Chen Lab Reposted

Out today from Jinmiao Chen's lab! Spatial Transcriptomics Analysis with topic Modeling to uncover spatial Patterns (STAMP) is a versatile and scalable method for dimension reduction in spatially resolved transcriptomics. nature.com/articles/s4159…

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Very excited to present STAMP: An Interpretable spatially aware dimension reduction of spatial transcriptomics nature.com/articles/s4159…


Great opportunity: snas.org.sg/saseaf. Please apply!


Jinmiao Chen Lab Reposted

Thrilled to report Patho-DBiT, just published in Cell 😊. It allows us to directly “see” all kinds of RNA species on the same clinical FFPE tissue slide, including mRNA, miRNA, snRNA, snoRNA, tRNA, etc, and splicing isoforms, genetic alterations (SNV, CNV, etc). Really a fun,…

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Awesome work.. Congratulations Dr. Rong Fan and team 🥳🎉💐

Today is the day 🤩. Thrilled to share our @Nature paper on Th2 function, CAR-T, & 8-year remission!⁩! Huge team effort w/⁦@GruppSteve⁩ ⁦⁦@carlhjune⁩ ⁦@MelenhorstLab⁩ ⁦@Tang_Lab_EPFL⁩, kudos to my postdoc ⁦@Zhiliang_Bainature.com/articles/s4158…



We are HIRING for Research Officer and PostDocs Interested in developing computational methods using AI for single cell and spatial omics ? Reach us at jinmiao@gmail.com Research Associate - careers.nus.edu.sg/job-invite/255… Research Fellow - careers.nus.edu.sg/job-invite/255…


Jinmiao Chen Lab Reposted

Read the Research Briefing on SpatialGlue here: nature.com/articles/s4159…

Out today from Jinmiao Chen's lab! SpatialGlue uses deep learning for integrating multimodal spatial omics data. Combining complementary modalities improves the discovery of spatial domains and the identification of cell subpopulations across tissues. nature.com/articles/s4159…

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Jinmiao Chen Lab Reposted

ezSingleCell: an integrated one-stop single-cell and spatial omics analysis platform for bench scientists | Nature Communications nature.com/articles/s4146…


Jinmiao Chen Lab Reposted

Many thanks to @vishuo for providing powerful servers for the ezSingleCell project 😊


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