A novel survival prediction signature outperforms PAM50 and artificial intelligence-based feature-selection methods

• Main Authors: Foo, Reuben Jyong Kiat, Tian, Siqi, Tan, Ern Yu, Goh, Wilson Wen Bin
• Other Authors: School of Chemical and Biomedical Engineering
• Format: Article
• Language: English
• Published: 2023
• Subjects: Science::Medicine; Science::Biological sciences; Breast Cancer; Data Science
• Online Access: https://hdl.handle.net/10356/165805
• Institution: Nanyang Technological University

The robustness of a breast cancer gene signature, the super-proliferation set (SPS), is initially tested and investigated on breast cancer cell lines from the Cancer Cell Line Encyclopaedia (CCLE). Previously, SPS was derived via a meta-analysis of 47 independent breast cancer gene signatures, bench...