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scAEGAN: Unification of single-cell genomics data by adversarial learning of latent space correspondences
Recent progress in Single-Cell Genomics has produced different library protocols and techniques for molecular profiling. We formulate a unifying, data-driven, integrative, and predictive methodology for different libraries, samples, and paired-unpaired data modalities. Our design of scAEGAN includes...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9897517/ https://www.ncbi.nlm.nih.gov/pubmed/36735690 http://dx.doi.org/10.1371/journal.pone.0281315 |