Congratulations to Jett and others in the lab for their new paper in Nature Communications introducing evaluation metrics, a gold-standard dataset, and a new probabilistic machine learning method to help infer single-cell expression profiles from multiplexed imaging datasets in the presence of segmentation errors.

Congratulations to Matt and the rest of the lab on their new preprint using scRNA-seq and a novel antibody screening strategy to design and validate antibody panels.

Congratulations to Vesal on his new preprint on how to design and evaluate protein bait subsets for BioID profiling.

Congratulations to Chengxin on his preprint showing how multicellular niches can be inferred from single-cell atlases and linking these to patient outcomes in pancreatic cancer.

Congratulations to Cindy and Alina for their paper Beyond benchmarking and towards predictive models of dataset-specific single-cell RNA-seq pipeline performance now published in Genome Biology.

Kieran will be giving a talk on Machine learning tools for the analysis and interpretation of highly multiplexed imaging data at Spatial Biology East Coast 2024.