Wesley Wei Qian

The paper develops a high-throughput imaging platform to assess the functional impact of missense variants on protein localization, finding that mislocalization is common in pathogenic variants.

The paper develops a Principal Odor Map using graph neural networks that matches human-level odor description performance and generalizes to diverse odor prediction tasks.

The paper identifies a molecular-level representation of odors that predicts receptor, neural, and behavioral responses across species and shows metabolic relationships in odor space.

This paper introduces ECNet, a deep learning model that uses evolutionary context to predict protein variant fitness, outperforming existing methods on multiple datasets.