Comparison of five supervised feature selection algorithms leading to top features and gene signatures from multi-omics data in cancer

BACKGROUND: As many complex omics data have been generated during the last two decades, dimensionality reduction problem has been a challenging issue in better mining such data. The omics data typically consists of many features. Accordingly, many feature selection algorithms have been developed. Th...

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Detalles Bibliográficos
Autores principales: Bhadra, Tapas, Mallik, Saurav, Hasan, Neaj, Zhao, Zhongming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9052461/
https://www.ncbi.nlm.nih.gov/pubmed/35484501
http://dx.doi.org/10.1186/s12859-022-04678-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9052461/
https://www.ncbi.nlm.nih.gov/pubmed/35484501
http://dx.doi.org/10.1186/s12859-022-04678-y

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