Jeyan Thiyagalingam

The paper introduces DPI-Score, a deep learning metric to assess protein-protein interfaces in cryo-EM structures, showing it can detect interface errors not found by density-based scores.

This paper introduces a deep learning method to improve single particle cryoEM data quality by automatically filtering noisy images using denoising and domain adaptation neural networks.

EMinsight captures and analyzes metadata from cryoEM single particle analysis experiments to improve instrument performance and data archiving.

The paper uses single-cell phenomics to study DVE cell migration in mouse embryos, revealing mechanical heterogeneities and how surrounding cells facilitate collective migration.

The paper introduces PI-score, a machine learning-based metric to assess protein-protein interfaces in cryo-EM-derived assemblies, identifying errors not captured by density-based methods.