Abstract
Analyzing Genomic profiles of prostate cancer patients with the similar metastatic site may unveil the progression mechanism of cancer and assist in the diagnose and the treatment of cancer. In this model, we propose a machine learning approach based on gene expression and copy number alterations for cohorts of prostate cancer with different metastatic sites.
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CITATION STYLE
El Amsy, T. (2019). Machine learning approach for predicting metastatic sites of prostate cancer. In ACM-BCB 2019 - Proceedings of the 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (p. 626). Association for Computing Machinery, Inc. https://doi.org/10.1145/3307339.3343477
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