Hartland Warren Jackson

The paper integrates multi-modal data to identify immune subgroups in RCC and suggests immunotherapy strategies based on distinct T cell communication networks.

The paper shows humanized PDX models preserve tumour-specific immune microenvironments, supporting their use for studying immune evasion mechanisms.

The paper identifies four epithelial transcription states in pancreatic cancer and links their origins to early developmental processes.

This study uses multi-modal VAEs to integrate multiple views of highly multiplexed imaging data, improving the prediction of clinical outcomes and identification of cell states.

Rakaia enables interactive exploration of spatial biology data through a browser-based platform, identifying cell types in non-malignant human breast tissue.

This study integrates spatial proteomics and genomics in PDAC to identify tumour-immune-stroma interactions and their genomic associations, showing multi-omics models improve patient survival prediction.

This study uses single-cell transcriptomics to show that hypoxia in organoid models influences transcriptional subtypes in pancreatic cancer.

The paper introduces a Bayesian optimization framework for automated registration of spatial expression data across modalities, achieving higher success rates on a large dataset of 954 image pairs.

STARLING quantifies cell populations from spatial protein expression data while accounting for segmentation errors, identifying known cell types and quantifying heterogeneity in human tonsil tissue.

The paper introduces Cytomarker, an interactive platform for designing antibody panels using single-cell RNA-seq data, and validates it on human mammary tissue subpopulations.

Astir assigns cell identities to single-cell imaging and proteomic data by integrating prior knowledge, outperforming existing methods in accuracy and scalability.

The paper introduces histoCAT, a tool for analyzing single-cell spatial omics data to explore cell phenotypes and interactions in tissues, demonstrating its application on human breast cancer mass cytometry images.