ACSNI: An unsupervised machine-learning tool for prediction of tissue-specific pathway components using gene expression profiles

Determining the tissue- and disease-specific circuit of biological pathways remains a fundamental goal of molecular biology. Many components of these biological pathways still remain unknown, hindering the full and accurate characterization of biological processes of interest. Here we describe ACSNI...

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Detalles Bibliográficos
Autores principales: Anene, Chinedu Anthony, Khan, Faraz, Bewicke-Copley, Findlay, Maniati, Eleni, Wang, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Descriptor
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8212143/
https://www.ncbi.nlm.nih.gov/pubmed/34179848
http://dx.doi.org/10.1016/j.patter.2021.100270

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8212143/
https://www.ncbi.nlm.nih.gov/pubmed/34179848
http://dx.doi.org/10.1016/j.patter.2021.100270

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