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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...
Tallennettuna:
| Julkaisussa: | Genomics |
|---|---|
| Päätekijät: | , , , , , , , , , |
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
2016
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| Aiheet: | |
| Linkit: | 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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