Accurate Prediction of Biological Assays with High-throughput Microscopy Images and Convolutional Networks

This repository contains code to reproduce the results of "Accurate Prediction of Biological Assays with High-throughput Microscopy Images and Convolutional Networks".

Dataset

The dataset used is based on the "Cell Painting Assay Dataset" (see https://github.com/gigascience/paper-bray2017 for download instructions). We also provide the subset of pre-processed images (in .npz format) used for our experiments here: https://ml.jku.at/software/cellpainting/dataset

Instructions

Configs

We use configuration files to set hyperparameters and directories, sample configurations are provided in the configs folder and have to be adjusted accordingly. Parameters from the configuration files can also be overwritten from the command line.

Training

python main.py --config <configfile> --gpu <gpu-id> --j <number of dataloading threads> --training.batchsize <bs>

Pre-trained Weights

Weights for the trained GapNet can be downloaded here: https://ml.jku.at/software/cellpainting/models/gapnet.pth.tar When using the provided script specify the path to the downloaded weights via the --checkpoint switch, e.g.:

python main.py --config <configfile> --gpu <gpu-id> --checkpoint <path-to-checkpoint> --j <number of dataloading threads> --training.batchsize <bs>