Datasets:
license: bsd-3-clause
pretty_name: JUMPCP subset for CS-ARM-BN
task_categories:
- image-classification
language:
- en
tags:
- cell-painting
- jump-cp
- microscopy
- biological-imaging
- image-analysis
- computer-vision
- plate-effects
Multi-Source Domain Adaptation for Bioimaging Data (MSCDA-BioIm)
MSCDA-BioIm is a biomedical microscopy benchmark for evaluating test-time and in-context domain adaptation under realistic batch effects. Built from the large-scale JUMP-CP dataset, it targets mechanism-of-action (MoA) classification using five-channel images of compounds associated with eight well-defined MoA classes. The dataset is organized by experimental batches and imaging sources, enabling controlled evaluation of generalization to unseen batches, cross-source transfer, small target context sizes, and label-shifted target batches.
A key feature of MSCDA-BioIm is the inclusion of negative control samples in every experimental batch. These unperturbed samples provide a stable reference for estimating batch-specific technical variation, making the dataset especially suitable for studying control-aware adaptation methods such as CS-ARM-BN.