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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...

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Detalles Bibliográficos
Autores principales: Khan, Sumeer Ahmad, Lehmann, Robert, Martinez-de-Morentin, Xabier, Maillo, Alberto, Lagani, Vincenzo, Kiani, Narsis A., Gomez-Cabrero, David, Tegner, Jesper
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
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