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Sparse representation learning derives biological features with explicit gene weights from the Allen Mouse Brain Atlas
Unsupervised learning methods are commonly used to detect features within transcriptomic data and ultimately derive meaningful representations of biology. Contributions of individual genes to any feature however becomes convolved with each learning step, requiring follow up analysis and validation t...
| 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/PMC9987823/ https://www.ncbi.nlm.nih.gov/pubmed/36877707 http://dx.doi.org/10.1371/journal.pone.0282171 |