Our Publications

Generative Bayesian Networks for Augmentation of Molecular Data from Commercial Genetic Panels

Reconstructing a latent representation of gene expression from genomic alterations to improve clinical utility of real-world clinicogenomics data

Reconstructing gene expression from clinical and genetic panel data for predictions of tumor microenvironment features and response to immune checkpoint inhibitor therapy.

Integrating drug structure and target binding affinity for improved prediction of survival in cancer patients treated with immune checkpoint inhibitors.

A systems biology-informed machine learning framework to predict drug response using clinically available NGS data.

Empowering Clinicians to Manage Chronic-comorbid Conditions by Predicting Adverse Outcomes with Transparent AI at the Point of Care.