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XA4C: eXplainable representation learning via Autoencoders revealing Critical genes
Machine Learning models have been frequently used in transcriptome analyses. Particularly, Representation Learning (RL), e.g., autoencoders, are effective in learning critical representations in noisy data. However, learned representations, e.g., the “latent variables” in an autoencoder, are difficu...
| 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/PMC10569512/ https://www.ncbi.nlm.nih.gov/pubmed/37782668 http://dx.doi.org/10.1371/journal.pcbi.1011476 |