binomialRF: interpretable combinatoric efficiency of random forests to identify biomarker interactions

BACKGROUND: In this era of data science-driven bioinformatics, machine learning research has focused on feature selection as users want more interpretation and post-hoc analyses for biomarker detection. However, when there are more features (i.e., transcripts) than samples (i.e., mice or human sampl...

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Detalles Bibliográficos
Autores principales: Rachid Zaim, Samir, Kenost, Colleen, Berghout, Joanne, Chiu, Wesley, Wilson, Liam, Zhang, Hao Helen, Lussier, Yves A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Methodology Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7456085/
https://www.ncbi.nlm.nih.gov/pubmed/32859146
http://dx.doi.org/10.1186/s12859-020-03718-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7456085/
https://www.ncbi.nlm.nih.gov/pubmed/32859146
http://dx.doi.org/10.1186/s12859-020-03718-9

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