Discovering Common miRNA Signatures Underlying Female-Specific Cancers via a Machine Learning Approach Driven by the Cancer Hallmark ERBB

Big data processing, using omics data integration and machine learning (ML) methods, drive efforts to discover diagnostic and prognostic biomarkers for clinical decision making. Previously, we used the TCGA database for gene expression profiling of breast, ovary, and endometrial cancers, and identif...

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Detalles Bibliográficos
Autores principales: Pane, Katia, Zanfardino, Mario, Grimaldi, Anna Maria, Baldassarre, Gustavo, Salvatore, Marco, Incoronato, Mariarosaria, Franzese, Monica
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9219956/
https://www.ncbi.nlm.nih.gov/pubmed/35740327
http://dx.doi.org/10.3390/biomedicines10061306

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9219956/
https://www.ncbi.nlm.nih.gov/pubmed/35740327
http://dx.doi.org/10.3390/biomedicines10061306

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