scTenifoldNet: A Machine Learning Workflow for Constructing and Comparing Transcriptome-wide Gene Regulatory Networks from Single-Cell Data

We present scTenifoldNet—a machine learning workflow built upon principal-component regression, low-rank tensor approximation, and manifold alignment—for constructing and comparing single-cell gene regulatory networks (scGRNs) using data from single-cell RNA sequencing. scTenifoldNet reveals regulat...

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Detalles Bibliográficos
Autores principales: Osorio, Daniel, Zhong, Yan, Li, Guanxun, Huang, Jianhua Z., Cai, James J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7733883/
https://www.ncbi.nlm.nih.gov/pubmed/33336197
http://dx.doi.org/10.1016/j.patter.2020.100139

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7733883/
https://www.ncbi.nlm.nih.gov/pubmed/33336197
http://dx.doi.org/10.1016/j.patter.2020.100139

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