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Combining strong sparsity and competitive predictive power with the L-sOPLS approach for biomarker discovery in metabolomics
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Document type | Article de périodique (Journal article) – Article de recherche |
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Access type | Accès restreint |
Publication date | 2017 |
Language | Anglais |
Journal information | "Metabolomics" - Vol. 13, no. 130, p. 15 (2017) |
Peer reviewed | yes |
Publisher | Springer New York LLC (New York) |
issn | 1573-3882 |
e-issn | 1573-3890 |
Publication status | Publié |
Affiliations |
UCL
- SSH/LIDAM/ISBA - Institut de Statistique, Biostatistique et Sciences Actuarielles UCL - SST/ICTM/ELEN - Pôle en ingénierie électrique |
Keywords | Biomarker discovery ; (O)PLS models ; Feature selection ; Sparse models ; L-sOPLS · 1H-NMR data ; RT-qPCR data |
Links |
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Bibliographic reference | Feraud, Baptiste ; Munaut, Carine ; Martin, Manon ; Verleysen, Michel ; Govaerts, Bernadette. Combining strong sparsity and competitive predictive power with the L-sOPLS approach for biomarker discovery in metabolomics. In: Metabolomics, Vol. 13, no. 130, p. 15 (2017) |
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Permanent URL | http://hdl.handle.net/2078.1/189217 |