Pipeline for particle picking in cryo-electron microscopy images using convolutional neural networks trained from positive and unlabeled examples. Also featuring micrograph and tomogram denoising with DNNs.

cryo-ET particle picking by representation and metric learning

TomoBEAR is a configurable and customizable modular pipeline for streamlined processing of cryo-electron tomographic data for subtomogram averaging.

TomoNet is a GUI based pipeline package focusing on cryoET and STA data processing

KLT picker: Particle picking using data-driven optimal templates (Python version)

Cellular content mining and particle localization

REliable PIcking by Consensus (REPIC) - an ensemble learning methodology for cryo-EM particle picking

Data analysis scripts, patches, and installation guides for cryo-EM particle pickers.

2D NN-based particle picking from sparse labels

Open Source python module to enable batch gold particle picking, filtering, processing & statistical modelling of TEM images produced by IGEM (immunogold electron microscopy).

KLT picker: Particle picking using data-driven optimal templates (MATLAB version)

Plot metrics from a Topaz training run

REliable PIcking by Consensus (REPIC)

Web application in Dash and Plotly.js for displaying cryo-EM micrographs and visualizing coordinate overlays.