Kristy A. Carpenter

This paper introduces PIGLET, a graph transformer method for drug-target interaction prediction that outperforms existing models on a drug-based split of the Human dataset.

The paper introduces a dataset of predicted binding pockets across the human proteome and a machine learning model to score and filter these pockets, outperforming existing methods.

This study evaluates LLMs' ability to infer biochemical reactions and disease associations from protein pathways, finding poor performance and introducing a benchmark dataset.

This study evaluates how training data composition affects protein structure analysis algorithms across three tasks, finding that including diverse structure types improves performance.