Developing a Prognostic Gene Panel of Epithelial Ovarian Cancer Patients by a Machine Learning Model

Epithelial ovarian cancer patients usually relapse after primary management. We utilized the support vector machine algorithm to develop a model for the chemo-response using the Cancer Cell Line Encyclopedia (CCLE) and validated the model in The Cancer Genome Atlas (TCGA) and the GSE9891 dataset. Fi...

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Detalles Bibliográficos
Autores principales: Lu, Tzu-Pin, Kuo, Kuan-Ting, Chen, Ching-Hsuan, Chang, Ming-Cheng, Lin, Hsiu-Ping, Hu, Yu-Hao, Chiang, Ying-Cheng, Cheng, Wen-Fang, Chen, Chi-An
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6406249/
https://www.ncbi.nlm.nih.gov/pubmed/30823599
http://dx.doi.org/10.3390/cancers11020270

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6406249/
https://www.ncbi.nlm.nih.gov/pubmed/30823599
http://dx.doi.org/10.3390/cancers11020270

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