BBBC021 NSC Accuracy
1 papers with code • 1 benchmarks • 1 datasets
BBBC021 is a dataset of fully imaged human cells. Cells are treated with one of 113 small molecules at 8 concentrations, and fluorescent images are captured staining for nucleus, actin and microtubules. The phenotypic profiling problem is presented, where the goal is to extract features containing meaningful information about the cellular phenotype exhibited. Each of 103 unique compound concentration treatment is labeled with a mechanism-of-action (MOA). The MOA is predicted for each unique treatment (averaging features over all treatment examples) by matching the MOA of the closest point excluding points of the same compound. The dataset and more information can be found at https://bbbc.broadinstitute.org/BBBC021.
Benchmarks
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CytoImageNet
Most implemented papers
CytoImageNet: A large-scale pretraining dataset for bioimage transfer learning
Motivation: In recent years, image-based biological assays have steadily become high-throughput, sparking a need for fast automated methods to extract biologically-meaningful information from hundreds of thousands of images.
