Kenny Roberts

TERRA is a foundation model for spatial transcriptomics that predicts tissue behavior under perturbation and identifies multi-scale biological insights across tissues.

This study uses spatial transcriptomics to map Pseudomonas aeruginosa niches in lung tissue from CF and COPD patients, revealing distinct bacterial states and host interactions linked to infection persistence.

This paper creates a detailed heart atlas using multimodal data to identify cell states and disease-associated genetic variants in specific heart regions.

This study optimizes Xenium in situ sequencing for PAXgene-fixed tissues, showing comparable or better spatial RNA detection than FFPE samples.

Human Developmental Cell Atlas integrates ~4.6 million cells/nuclei from 4-22 post-conception weeks into 454 refined cell types and maps 114 spatial niches across 6PCW whole-embryo sections.

Tripso, a self-supervised transformer model, identifies gene program-specific embeddings and discovers novel gene programs, revealing biological insights in hematopoietic development and disease.

This study creates a spatially-resolved molecular atlas of human skin and uses deep learning to identify 26 niches, revealing novel immune memory structures in inflammatory skin diseases.

DISCO-seq enables 3D single-cell transcriptomics of whole tissues and organisms by combining tissue-clearing chemistry with imaging and transcriptomic profiling.

The paper presents a spatial transcriptomic atlas of autism-associated genes in the developing human brain, identifying convergence in the thalamus and germinal zones.

This study creates a spatial genomics atlas of human skin fibroblasts in health and disease, identifying six major populations and three disease-specific subtypes.

This study uses single-cell transcriptomics to compare in vitro and in vivo chondrocyte differentiation, identifies off-target differentiation, and improves in vitro protocols by inhibiting FOXO1.

MintFlow is a generative AI algorithm that predicts how tissue perturbations reprogram cell states in disease, revealing novel cell populations and therapeutic targets in three human conditions.

The paper identifies a spatiotemporal cancer cell trajectory in glioblastoma that explains tumor heterogeneity across regions and subclones.

This study integrates single-cell and spatial transcriptomics with histopathology to identify cellular and molecular changes in lung alveolar damage during COVID-19 progression.

This study creates a single-cell spatial atlas of the developing human reproductive tract, identifying genes and mechanisms involved in sexual dimorphism and organ development.

WebAtlas integrates single cell and spatial transcriptomic data into a cloud-optimised format for interactive exploration.

This study constructs a multiomic atlas of human early skeletal development using single-nuclei transcriptomics, epigenomics, and spatial transcriptomics to uncover regulatory mechanisms and cell states involved in bone and joint formation.

This study develops a multi-omic reference of human cardiac development and identifies disruptions in Trisomy 21 hearts.

This paper creates a human embryonic limb cell atlas using single-cell and spatial transcriptomics, identifying novel cell populations and developmental patterns.

This study creates a prenatal human skin cell atlas, revealing immune cells' role in skin development and showing their impact on vascular and hair follicle formation.

This study creates a spatially resolved single-cell multiomics atlas of human trophoblast differentiation in early pregnancy, revealing key regulatory programs and cell-cell communication events involved in EVT invasion and arterial transformation.

This study maps the temporal and spatial dynamics of the human endometrium using single-cell and spatial reference maps, identifying key signaling pathways regulating cell fate in vivo and in vitro.

PoSTcode improves transcript decoding from spatial transcriptomic images by reducing mislabeling and doublet signals.

This paper introduces a new spatial transcriptomic technology, WTA, and applies it to map the cellular architecture of the developing human neocortex, showing spatial enrichment of autism-related genes.

The paper characterizes the cellular composition and gene expression of the adult human heart using single-cell transcriptomics, identifying distinct cell types and their functional roles.