DeepProfiler
Table of Contents
DeepProfiler uses deep neural networks to extract morphological features directly from raw microscopy images, bypassing traditional segmentation-and-measurement pipelines. It is designed for high-throughput screens where deep learning representations outperform classical feature sets.
Key capabilities:
- Train and apply convolutional neural networks for feature extraction
- Support for EfficientNet, ResNet, and custom architectures
- Crop and embed single cells from large microscopy images
- Produce embeddings compatible with pycytominer and downstream profiling workflows
Publication #
Nature Communications · 2024
Learning representations for image-based profiling of perturbations
Moshkov N, Bornholdt M, Benoit G, Smith K, et al.