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Network-based penalized regression with application to genomic data
Penalized regression approaches are attractive in dealing with high-dimensional data such as arising in high-throughput genomic studies. New methods have been introduced to utilize the network structure of predictors, e.g. gene networks, to improve parameter estimation and variable selection. All th...
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| Asıl Yazarlar: | , , |
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| Materyal Türü: | Artigo |
| Dil: | Inglês |
| Baskı/Yayın Bilgisi: |
2013
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| Konular: | |
| Online Erişim: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4007772/ https://ncbi.nlm.nih.gov/pubmed/23822182 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1111/biom.12035 |
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