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Computational identification of surrogate genes for prostate cancer phases using machine learning and molecular network analysis
BACKGROUND: Prostate cancer is one of the most common malignant diseases and is characterized by heterogeneity in the clinical course. To date, there are no efficient morphologic features or genomic biomarkers that can characterize the phenotypes of the cancer, especially with regard to metastasis –...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2014
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4159107/ https://www.ncbi.nlm.nih.gov/pubmed/25151146 http://dx.doi.org/10.1186/1742-4682-11-37 |