Orr Ashenberg

StriMap models TCR-peptide-HLA interactions using structural and sequence features, achieving state-of-the-art performance and identifying disease-associated peptides in ankylosing spondylitis.

The paper maps chemokine landscapes in solid tumors using spatial transcriptomics, identifying conserved and tumor-specific patterns and revealing perivascular CCR7 dendritic cells as key sources of lymphocyte-attracting chemokines.

TissueFormer is a foundation model that predicts spatial gene expression from histology images at single-cell resolution and scales to diagnostic tasks.

The paper presents a machine learning challenge to predict gene perturbation effects on T cell differentiation, finding that feature representation from perturbational data improves performance and validating top genes experimentally.

This study identifies IL13 as a survival factor for Hodgkin lymphoma cells by analyzing the tumor microenvironment with spatial and single-cell resolution.

The paper uses population-scale single-nucleus ATAC-seq and RNA-seq to identify regulatory variants and their disease associations in immune cells.

SlideCNA detects spatial copy number alterations from Slide-seq data to identify sub-clones in metastatic breast cancer.

The paper identifies genetic variants affecting innate lymphoid cells in the gut using single-cell RNA-seq and validates their regulatory roles across cell types.

This study creates a single-nucleus and spatial transcriptomic atlas of the COVID-19 liver, revealing cellular and functional disruptions associated with organ damage.

This study introduces STAG-seq, a method combining transcriptomics and genotyping to functionally analyze genetic variants in immune cells, revealing their impact on gene expression and disease mechanisms.

This study uses single-cell RNA-sequencing to analyze fetal bone marrow development and identifies disruptions in hematopoiesis in Down syndrome.

This study creates a single-cell and spatial atlas of autopsy tissues from COVID-19 patients, revealing altered cellular responses and potential therapeutic targets.

This study uses single-nucleus and spatial transcriptomics to analyze pancreatic cancer before and after neoadjuvant treatment, revealing changes in cell states and immune infiltration that may inform therapy.

Cumulus is a cloud-based framework for analyzing large-scale sc/snRNA-seq data, improving efficiency and scalability while maintaining result quality.

The paper develops a toolbox for scRNA-Seq and snRNA-Seq of fresh and frozen human tumors, testing it across eight tumor types and optimizing protocols for different tissue characteristics.

Across 1,176,683 airway and lung cells from 22 datasets, ACE2 rises with age, in males and in smokers' multiciliated cells, and is lowest in young children.