Triple-effect correction for Cell Painting data with contrastive and domain-adversarial learning
Abstract Cell Painting (CP), as a high-throughput imaging technology, generates extensive cell-stained imaging data, providing unique morphological insights for biological research. However, CP data contains three types of technical effects, referred to as triple effects, including batch effects, gr...
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| المؤلفون الرئيسيون: | , , , , , , , , , , |
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| التنسيق: | Artigo |
| اللغة: | Inglês |
| منشور في: |
Nature Portfolio
2025-07-01
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| سلاسل: | Nature Communications |
| الوصول للمادة أونلاين: | https://doi.org/10.1038/s41467-025-62193-z |
| الوسوم: |
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