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Feature weight estimation for gene selection: a local hyperlinear learning approach
BACKGROUND: Modeling high-dimensional data involving thousands of variables is particularly important for gene expression profiling experiments, nevertheless,it remains a challenging task. One of the challenges is to implement an effective method for selecting a small set of relevant genes, buried i...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2014
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4007530/ https://www.ncbi.nlm.nih.gov/pubmed/24625071 http://dx.doi.org/10.1186/1471-2105-15-70 |