Jonathan Schwartz

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.

High accuracy fluorescence-guided cryo-focused ion beam milling

This paper introduces two fluorescence-guided cryo-FIB milling workflows to improve targeting accuracy for cryo-ET, enabling routine capture of structures across spatial scales.

Decoding Bispecific Antibody Developability: Design Rules and Predictive Models from a 160-Member Library

This paper analyzes 160 bispecific antibodies and their parental arms to identify developability inheritance patterns and predictive models for bispecific antibody design.

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.

Characterization Standard for In-situ Cryo-electron Tomography

The paper introduces PP7 virus-like particles as a standardized benchmark for cryo-electron tomography, enabling rapid validation and resolution assessment of tomographic pipelines.

Open-source Tools for CryoET Particle Picking Machine Learning Competitions

The paper introduces open-source tools for a machine learning competition focused on particle picking in cryo-electron tomography data.

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.