Excited to share our new work integrating KPtracer with spatial techniques nature.com/articles/s41588-0…. A team effort of @MattG_Jones @dianyang1117 @insitubiology @JswLab @YosefLab. A long but incredible journey working with @MattG_Jones, who started at @MIT and recruiting!

A central limitation of cellular barcoding analyses has been the loss of native spatial context. With @insitubiology, we developed an adaptable platform for multiclonal lineage analysis that links clonal history to spatially resolved gene expression. cell.com/cell-stem-cell/full…

I'm excited to share our new preprint "Vermeer: Autoregressive generative modeling of microscopy predicts protein localization," a collaboration between @MSFTResearch and @insitubiology! Preprint: biorxiv.org/content/10.64898… Protein localization is fundamental to protein function, but experimental imaging, a key technique to study localization, cannot scale to the entire human proteome across all biological contexts. To address this challenge, we introduce Vermeer, an autoregressive generative model trained on Human Protein Atlas data @ProteinAtlas. Vermeer synthesizes fluorescence microscopy images of proteins conditioned on cell morphology reference stains and protein sequence embeddings (ESM-C). Vermeer can leverage latent information about protein localization in the ESM embeddings to generalize to proteins the model has never seen during training. (1/n)

1/ Excited to share our preprint on the Cancer Immunotherapy Machine Learning Competition: broad.io/MLC-2023 - the first of the ongoing @SchmidtCenter Cell Perturbation Prediction Challenge (CPPC) series. Here are some key points! 🧵👇