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GAN-based data augmentation for transcriptomics: survey and comparative assessment
MOTIVATION: Transcriptomics data are becoming more accessible due to high-throughput and less costly sequencing methods. However, data scarcity prevents exploiting deep learning models’ full predictive power for phenotypes prediction. Artificially enhancing the training sets, namely data augmentatio...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Oxford University Press
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10311334/ https://www.ncbi.nlm.nih.gov/pubmed/37387181 http://dx.doi.org/10.1093/bioinformatics/btad239 |