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Meta-analytic framework for sparse K-means to identify disease subtypes in multiple transcriptomic studies
Disease phenotyping by omics data has become a popular approach that potentially can lead to better personalized treatment. Identifying disease subtypes via unsupervised machine learning is the first step towards this goal. In this paper, we extend a sparse K-means method towards a meta-analytic fra...
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| Опубликовано в: : | J Am Stat Assoc |
|---|---|
| Главные авторы: | , , , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
2016
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4908837/ https://ncbi.nlm.nih.gov/pubmed/27330233 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/01621459.2015.1086354 |
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