Antanaviciute Group: Computational Biology and Tissue Immunology

agne.antanaviciute@rdm.ox.ac.uk

Spatial transcriptomics analysis visualising immune infiltration in the small intestine of a patient with necrotising enterocolitis

Data-Driven Systems Immunology

We leverage large-scale single-cell omics datasets to uncover fundamental principles of tissue immunity in health and inflammation. By integrating transcriptomic, epigenomic and proteomic data, we apply systems-level and computational approaches to map immune cell states, interactions and regulatory programs within tissue microenvironments.

Early-Life Intestinal Immunity and Inflammation

We investigate how the human intestinal immune system develops from fetal stages through early childhood, using multi-modal single-cell and spatial omics approaches. By mapping immune and epithelial cell programs in both healthy development and disease, we aim to understand how disruptions in early-life immune trajectories contribute to conditions such as necrotising enterocolitis. Our work connects fundamental developmental immunology with the mechanisms of tissue-level inflammation in neonates.

Computational Methods for Spatial Omics

Our group develops novel computational and machine learning tools to analyse and interpret spatial omics data. We focus on methods that capture cellular organization, spatial interactions and tissue architecture across diverse spatial technologies and disease contexts.

Predictive Modelling from Imaging and Molecular Data

We integrate high-resolution histological imaging with single-cell and spatial molecular datasets to build predictive models of tissue biology. This includes machine learning frameworks that infer transcriptomic features from histopathology, with the aim of bridging traditional pathology with molecular precision diagnostics.