Optimal dimensionality selection for independent component analysis of transcriptomic data

BACKGROUND: Independent component analysis is an unsupervised machine learning algorithm that separates a set of mixed signals into a set of statistically independent source signals. Applied to high-quality gene expression datasets, independent component analysis effectively reveals both the source...

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Detalles Bibliográficos
Autores principales: McConn, John Luke, Lamoureux, Cameron R., Poudel, Saugat, Palsson, Bernhard O., Sastry, Anand V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8653613/
https://www.ncbi.nlm.nih.gov/pubmed/34879815
http://dx.doi.org/10.1186/s12859-021-04497-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8653613/
https://www.ncbi.nlm.nih.gov/pubmed/34879815
http://dx.doi.org/10.1186/s12859-021-04497-7

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