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...

Descripción completa

Detalles Bibliográficos
Autores principales: Abbasi, Mohammad, Sanderford, Connor R., Raghu, Narendiran, Pasha, Mirjeta, Bartelle, Benjamin B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Research Article
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

Internet

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

Ejemplares similares