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...

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Detalles Bibliográficos
Autores principales: Wu, Dingming, Wang, Dongfang, Zhang, Michael Q., Gu, Jin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Methodology Article
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

Internet

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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