Jonathan Warrell

Generative AI Guided Design of High-Affinity T cell Receptors

This paper introduces TCRPPO2, an AI-driven framework for optimizing TCR affinity, showing improved activity in engineered TCRs against tumor antigens.

A Variational Graph Partitioning Approach to Modeling Protein Liquid-liquid Phase Separation

This paper introduces a Graph Partitioned GNN (GP-GNN) to predict protein liquid-liquid phase separation by focusing on subgraphs containing intrinsically disordered regions.

Dynamic convergence of neurodevelopmental disorder risk genes across neurodevelopment

This study identifies convergent biological pathways in mature neurons affected by neurodevelopmental disorder risk genes and shows drug candidates can ameliorate behavioral phenotypes.

Predicting Spatially Resolved Gene Expression via Tissue Morphology using Adaptive Spatial GNNs

This paper predicts spatial gene expression from histological images using adaptive spatial GNNs, improving performance on breast cancer data.

Single-cell genomics and regulatory networks for 388 human brains

The paper processes single-nuclei multi-omics data from 388 human brains to identify regulatory elements and build cell-type networks, revealing changes in aging and neuropsychiatric disorders.

Insights from Incorporating Quantum Computing into Drug Design Workflows

This paper introduces HypaCADD, a hybrid classical-quantum workflow for drug design that uses quantum machine learning to predict mutation impacts, showing performance comparable to classical methods.

Compression-based Network Interpretability Schemes

The paper investigates compression-based methods for interpreting deep learning models in cancer and psychiatric genomics, showing that compression quality can be assessed using generalization error and PAC-Bayes bounds.

An integrative ENCODE resource for cancer genomics

The paper develops a custom ENCODE annotation for cancer genomics, highlighting TF-RBP interactions and network rewiring during oncogenesis, and validates findings using experimental assays.

DypFISH: Dynamic Patterned FISH to Interrogate RNA and Protein Spatial and Temporal Subcellular Distribution

DypFISH quantitatively investigates spatial and temporal subcellular localization of RNA and protein using micropatterning and fluorescence microscopy, revealing reproducible patterns and dynamics.

Passenger mutations in 2500 cancer genomes: Overall molecular functional impact and consequences

The paper analyzes 2500 cancer genomes to assess the molecular functional impact of mutations, finding that some putative passenger variants may influence gene activity and contribute to cancer phenotypes.