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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...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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BioMed Central
2022
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| Materias: | |
| 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 |