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Fast dimension reduction and integrative clustering of multi-omics data using low-rank approximation: application to cancer molecular classification
BACKGROUND: One major goal of large-scale cancer omics study is to identify molecular subtypes for more accurate cancer diagnoses and treatments. To deal with high-dimensional cancer multi-omics data, a promising strategy is to find an effective low-dimensional subspace of the original data and then...
Autores principales: | Wu, Dingming, Wang, Dongfang, Zhang, Michael Q., Gu, Jin |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4667498/ https://www.ncbi.nlm.nih.gov/pubmed/26626453 http://dx.doi.org/10.1186/s12864-015-2223-8 |
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