James R. Heath

CytoRipple identifies tissue-level polarization vector fields from spatial multi-omic data to reveal multi-cellular structures and their functional associations.

This study shows EBV reprograms B cells in COVID-19 patients, leading to autoimmune-like features such as autoantibodies and dysregulated lipid profiles, similar to lupus and multiple sclerosis.

This paper uses surprisal information-theoretic analysis on spatial transcriptomic data from human glioblastoma to uncover hidden spatial programs and interactions not detected by standard methods.

This study identifies NF-κB-driven chromatin remodeling as a mechanism for drug-induced dedifferentiation in cancer, revealing its role in promoting drug-tolerant persister states.

The paper identifies a conserved immune signature linked to infection severity, risk factors, and treatment response using multi-cohort transcriptomic and proteomic data.

The paper introduces Tarpon, a generative AI model that synthesizes TCR atlases to uncover T cell behavior patterns and cross-dataset mappings of T cell states.

The paper develops a high-throughput platform to profile antigen-specific CD4+ T cells at single-cell resolution, identifying immunogenic features and functional heterogeneity in viral and cancer contexts.

The paper investigates early signaling and transcriptional changes in melanoma cells under BRAF inhibitor treatment, identifying SFK activation as a compensatory mechanism and demonstrating its sensitivity to co-inhibition.

The paper uses CITE-seq to analyze NK cell alterations in CAD patients, finding SPON2/IFNG ratio and adaptive NK cell signatures correlate with disease severity and inflammation.

APMAT analysis links CD8 T cell receptors, cognate antigens, and T cell phenotype/persistence using integrated experimental-computational methods.

This study uses spatial profiling to show immune suppression and microenvironment changes in fallopian tube precursors of high-grade serous ovarian cancer.

This study examines the relationship between T cell receptor (TCR) metrics and COVID-19 disease severity, finding significant associations that vary by TCR subset and collection timing.

This paper benchmarks HLA genotype prediction from single-cell RNA-seq data against molecular genotyping, showing improved accuracy with composite models and meta-analytic approaches.

The paper identifies rare loss-of-function variants in type I IFN immunity genes associated with severe COVID-19, particularly in younger patients with recessive inheritance.