Bob Chen

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.

The paper builds a dictionary of human intestinal organoid responses to 81 secreted niche factors using scRNA-seq, mapping perturbations and identifying cell type-specific pathways in an IBD context.

SpatialAgent integrates large language models with dynamic tool retrieval, multimodal interpretation, and claim verification to automate end-to-end spatial biology workflows from gene-panel design to tissue annotation and hypothesis generation.

This study maps tumor evolution and microenvironment dynamics in colorectal cancer using spatial multi-omic data, identifying key genes associated with immune exclusion and prognosis.

The paper develops contamination-focused metrics and software to optimize scRNA-seq experiments by reducing ambient contamination through experimental adjustments.

dropkick improves scRNA-seq quality control by automatically distinguishing real cells from ambient barcodes, outperforming existing methods in recovering rare cell types and excluding noise.

The paper introduces a dual-indexed library design for scRNA-seq to improve sequencing quality and throughput on high-throughput sequencers.

This paper introduces sc-UniFrac, a framework to quantify compositional diversity in cell populations across single-cell transcriptome datasets, demonstrating its utility in various applications.