David Richmond

The paper introduces CellMAPP and CHART to analyze multiplexed antibody imaging data, revealing modular morphological programs in response to genetic perturbations.

SCALLOPS improves processing of optical pooled screens by enabling efficient alignment and analysis of large-scale image data, demonstrating superior performance over existing methods.

The paper introduces PhenoCompass, a model for virtual phenotypic screening that identifies novel PI3K/mTOR inhibitors from a large compound library.

This study uses dynamic caging to link live-cell behavior with transcriptional responses across perturbations, revealing new insights into immune and inflammatory gene regulation.

The paper develops a framework to decode TLS maturation in NSCLC using spatial omics data and deep learning, identifying two distinct spatial ecosystems linked to patient outcomes.

Tangram2 maps cell-to-cell communication by integrating spatial transcriptomics with single-cell RNA sequencing to identify gene expression changes driven by neighboring cell types.

PRESAGE predicts perturbation expression responses using gene embeddings and outperforms existing methods in functional evaluations.

PerturbView enables highly multiplexed optical pooled screens in primary cells and tissues by improving barcode amplification, revealing regulators of NFκB signaling and enabling spatial transcriptomics integration.

The paper introduces a contrastive analysis framework to disentangle perturbation effects from natural cell variation in optical pooled screens, showing improved performance in generating embeddings and reducing technical artifacts.

This study uses a synthetic gene oscillator to analyze bacterial growth dynamics in the gut under healthy and inflammatory conditions, revealing variability in single-cell behavior.

The paper shows that a dynamically scaling gradient in the presomitic mesoderm regulates somite size control in zebrafish embryos.

The paper introduces software bots for analyzing image-based transcriptomic data, offering algorithms for nuclei segmentation and spot detection, with a machine learning model for challenging segmentation tasks.