Ariana Peck

Lessons learned from a Kaggle challenge for particle picking in cryo-electron tomography

The paper describes a Kaggle challenge for particle picking in cryo-electron tomography, resulting in improved algorithms and highlighting the need for better annotation quality measures.

AreTomoLive: Automated reconstruction of comprehensively-corrected and denoised cryo-electron tomograms in real-time and at high throughput

AreTomo3 and DenoisET form an automated GPU pipeline that reconstructs cryo-electron tomograms with tile-based contrast transfer function correction, screens their quality, and denoises them during acquisition.

Unsupervised learning of structural variability in cryo-EM data using normal mode analysis of deformable atomic models

The paper introduces an unsupervised method to analyze structural variability in cryo-EM data by deforming atomic models using normal mode analysis directly against 2D data, improving accuracy and interpretability.

Annotating CryoET Volumes: A Machine Learning Challenge

The paper introduces a phantom sample and annotated 3D volumes for a machine learning challenge to improve cryoET volume annotation.