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A Robust and Accurate Method for Feature Selection and Prioritization from Multi-Class OMICs Data
Selecting relevant features is a common task in most OMICs data analysis, where the aim is to identify a small set of key features to be used as biomarkers. To this end, two alternative but equally valid methods are mainly available, namely the univariate (filter) or the multivariate (wrapper) appro...
Gorde:
| Egile Nagusiak: | , , , , |
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| Formatua: | Artigo |
| Hizkuntza: | Inglês |
| Argitaratua: |
Public Library of Science
2014
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| Gaiak: | |
| Sarrera elektronikoa: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4172658/ https://ncbi.nlm.nih.gov/pubmed/25247789 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0107801 |
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