Assistant Professor @MassGeneralNews @harvardmed, Associate Member @broadinstitute @ragoninstitute | Decoding and translating the languages of biology
Boston, MA
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Chemical and transcriptomic barcodes of cellular senescence 🔬
RamanOmics integrates Raman imaging with spatial transcriptomics to map senescent cell states and their molecular signatures across aging and wound repair.
@NIH_CommonFund @sennetresearch
Online now!✨@kezhang2021 @xingjchen7 @f_monticolo @Salvato88775199 et al pair Raman imaging with spatial and single cell transcriptomics in aging and repair, and identify a lipid-linked Raman signature of p21+ cells @JianShuLab nature.com/articles/s43587-0…
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20 years after iPSCs: can AI take us from #CellReprogramming to #DeNovoCellDesign?
Since grad school, I’ve spent years searching for new reprogramming cocktails. The lesson: biology has two big challenges—#Scale and #Time.
We can’t test or sequence everything. And cells are dynamic systems—we need to model how they change over time.
In my recent talk, “When Cellular Reprogramming Meets AI,” I discuss how AI + live-cell measurement + perturbation could move us from observing cells → predicting trajectories → inverse-designing new cell states.
🎥 Full talk: vimeo.com/1211746570/1519f89…
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VIP-OT: When perturbation meets vibrational imaging and optimal transport | After introducing optimal transport to single-cell genomics in 2019, we’re excited to bring OT to the field of vibrational imaging for the first time. 🥳 biorxiv.org/content/10.64898…
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We are excited to share RamanOmics, the first multimodal framework integrating snRNA-seq, spatial transcriptomics, and label-free Raman imaging to map the spatial biochemical–molecular architecture of aging, senescence, and tissue repair. #NIH SenNet biorxiv.org/content/10.64898…
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Bering: joint cell segmentation and annotation for spatial transcriptomics with transferred graph embeddings nature.com/articles/s41467-0…
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When cellular reprogramming meets AI: towards de novo cell design | Nature Reviews Genetics nature.com/articles/s41576-0…
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Excited to share an update on our collaboration with Aviv Regev and Collin Stultz, led by Charles Comiter: predicting single-cell spatial transcriptomics from H&E images using SCHAF. New models, new datasets, and new discoveries. biorxiv.org/content/10.1101/…
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The placenta is one of the most complex and fascinating, yet least studied, human organs. A wonderful collaboration with the amazing members of the Haider and Chen @insitubiology labs. #placenta #HCA #Hiring
The spatial single-cell multiomic atlas of the first trimester human #placenta at molecular resolution provides a blueprint for future studies on early #PlacentalDevelopment and #pregnancy. #HCA @insitubiology @JianShuLab @harvardmed
nature.com/articles/s41591-0…
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We are excited to publish a spatially resolved single-cell multi-omic census of the placenta, contributing to the @humancellatlas project. The placenta plays an essential role in maintaining a healthy pregnancy, yet its function remains poorly understood. nature.com/articles/s41591-0…
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Jian Shu retweeted
The Human Cell Atlas initiative has the monumentally ambitious goal of cataloguing every cell type in the human body, from development to old age, and it is remarkable go.nature.com/411zuwx
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Jian Shu retweeted
We are thrilled to share an HCA Collection of 40+ peer-reviewed papers in @NaturePortfolio shedding light on human development, healthy and disease biology and vital analytical tools. #HCA2024NatureCollection #HumanCellAtlas nature.com/immersive/d42859-…
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Excited to share VIBRANT, a new modality and platform for drug discovery using infrared imaging⚡️#drugdiscovery #imaging #ai
Check out the latest publication from our group! VIBRANT: spectral profiling for single-cell drug responses
nature.com/articles/s41592-0…
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Excited to share our latest collaborative work, Raman2RNA (R2R)! 🚀 Our long-term mission: Build AI models to 'generate' and 'predict' single-cell multi-omics data, evolving biology from 'mapping' to 'mapping+generation and prediction'. 🧬🤖 #DigitalBiology #TeamScience #Hiring
Prediction of single-cell RNA expression profiles in live cells by Raman microscopy with Raman2RNA go.nature.com/4b25IKC
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We're excited to share Bering, a graph neural network that harnesses subcellular gene colocalization graphs and transfer embeddings for joint cell segmentation and annotation for spatial transcriptomics. @Kang_Jin__ @Oxer22 @tangjianpku @brucearonow We welcome your feedback.
How to decipher subcellular gene patterns in spatial transcriptomics data?
We're excited to share Bering, a graph neural network that harnesses subcellular gene colocalization graphs and transfer embeddings for joint cell segmentation and annotation (1/n)
biorxiv.org/content/10.1101/….
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Come join Charles @cscomiter on a venture to build novel generative models to “generate” single-cell multi-omics data from various imaging modalities and more. #Hiring
This is wild and a complete rethinking of H&E analysis—Aviv Regev’s lab developed a AI-based method for in silico generation of spatially resolved transcriptomic data from an H&E stain. It infers accurate spatial gene expression measured by MERFISH. biorxiv.org/content/10.1101/…
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Jian Shu retweeted
The creativity behind SCHAF will set the stage for a slew of works relating imaging and omics data. Come join Charles on a new venture to build a “DALL-E” for biology to generate multi-omics data from various novel imaging modalities for large-scale tissue mapping. We are hiring.
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I am ecstatic to share the most recent work of my first PhD student Charles Comiter with Aviv Regev. Charles started this challenging work with Aviv when he was an undergraduate student at Yale.
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Jian Shu retweeted
Thrilled to share my primary PhD work: a Transcription Factor Atlas for understanding gene regulation and cell engineering @CellCellPress. We created a comprehensive TF ORF library and applied it to profile resulting expression changes. A thread 1/X sciencedirect.com/science/ar…
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