Jian Shu

Assistant Professor @MassGeneralNews @harvardmed, AM @broadinstitute | Decoding and translating the languages of biology

[Jian Shu @JianShuLab]

VIP-OT introduces a new direction in building AI virtual cell. It couples high-dimensional, low-cost, nondestructive vibrational (chemical) imaging with optimal transport to infer single cell biochemical state dynamics and perturbation response trajectories and combinations.

[Jian Shu @JianShuLab]

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. 🥳 https://t.co/JfxJROCl0Z

[Jian Shu @JianShuLab]

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 https://t.co/IruMYEVEcH

[Jian Shu @JianShuLab]

Bering: joint cell segmentation and annotation for spatial transcriptomics with transferred graph embeddings https://t.co/E5kBdaLNUK

[Jian Shu @JianShuLab]

When cellular reprogramming meets AI: towards de novo cell design | Nature Reviews Genetics https://t.co/RKvPswCel9

[Jian Shu @JianShuLab]

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. https://t.co/ZCLAnzFHsr

[Jian Shu @JianShuLab]

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

[Nature Medicine @NatureMedicine]

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
https://t.co/qxR1KDc9TG

[Jian Shu @JianShuLab]

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. https://t.co/eqT8m0JgdK

[nature @Nature]

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 https://t.co/rbdBU9He8Q

[Human Cell Atlas @humancellatlas]

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 https://t.co/TKWn8CjXRd

[Jian Shu @JianShuLab]

Excited to share VIBRANT, a new modality and platform for drug discovery using infrared imaging⚡️#drugdiscovery #imaging #ai

[MinLab@ColumbiaUniv. @TheMinLab]

Check out the latest publication from our group! VIBRANT: spectral profiling for single-cell drug responses
https://t.co/Yqt7iY0DuF

[Jian Shu @JianShuLab]

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

[Nature Biotechnology @NatureBiotech]

Prediction of single-cell RNA expression profiles in live cells by Raman microscopy with Raman2RNA https://t.co/tMWuaOOX7x

[Jian Shu @JianShuLab]

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.

[Kang Jin @Kang_Jin__]

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)
https://t.co/qp2MvJVJ0g.

[Jian Shu @JianShuLab]

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

[Jiang He @JiangHe_PhD]

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. https://t.co/meOW9dcnj8

[Jian Shu @JianShuLab]

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.

[Jian Shu @JianShuLab]

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.

[Jian Shu @JianShuLab]

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.

[Julia Joung @JuliaJoung]

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 https://t.co/PPcJ0HZEsW

[Mass General Brigham Research @MGBResearchNews]

Congrats to Jian Shu, PhD, of the Department of Dermatology, who received an NIH New Innovator Award DP2 with the HEAL Initiative for his project, Scale Up Single-Cell Technologies to Map Pain-Associated Genes and Cells Across the Lifespan!
https://t.co/3w3ekQrhi7

[Jian Shu @JianShuLab]

Interested in decoding and reprogramming cellular senescence/aging? Join us: 👉 https://t.co/LeCjRvm5Tj

[NIH Common Fund @NIH_CommonFund]

Several awards have been issued to help our Cellular Senescence Network get one step closer to understanding how #SenescentCells in mice and humans impact #health, #aging, and #disease: https://t.co/RTLfzQrW1f. #SenNet