Jonathan R. Dry

This study identifies immunogenomic drivers of acquired resistance to immunotherapy across multiple cancer types using a large-scale clinicogenomic dataset.

The paper introduces a network biology-driven simulation method to predict effective drug combinations and identify biomarkers for DNA Damage Response inhibitors using cancer cell avatars.

SpinAdapt is an unsupervised RNA correction algorithm that enables transfer of molecular models between labs without requiring patient-level data, improving reproducibility and privacy.

The paper develops workflows to predict drug synergy based on target functional similarity and validates them in breast and colorectal cancer cell lines.

Deep Purity (DePuty) uses convolutional neural networks to predict tumor purity from SNP-based copy number and minor allele frequency data without matched normals, outperforming existing methods with fewer samples.