A novel algorithm for network-based prediction of cancer recurrence

To develop accurate prognostic models is one of the biggest challenges in ”omics”-based cancer research. Here, we propose a novel computational method for identifying dysregulated gene subnetworks as biomarkers to predict cancer recurrence. Applying our method to the DNA methylome of endometrial can...

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Detalhes bibliográficos
Publicado no:Genomics
Main Authors: Ruan, Jianhua, Jahid, Md Jamiul, Gu, Fei, Lei, Chengwei, Huang, Yi-Wen, Hsu, Ya-Ting, Mutch, David G., Chen, Chun-Liang, Kirma, Nameer B., Huang, Tim H.-M.
Formato: Artigo
Idioma:Inglês
Publicado em: 2016
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Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC5253120/
https://ncbi.nlm.nih.gov/pubmed/27453286
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.ygeno.2016.07.005
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