A novel survival prediction signature outperforms PAM50 and artificial intelligence-based feature-selection methods
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...
Saved in:
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: | |
Online Access: | https://hdl.handle.net/10356/165805 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
What can scatterplots teach us about doing data science better?
by: Goh, Wilson Wen Bin, et al.
Published: (2022) -
Multiple signatures of a disease in potential biomarker space : getting the signatures consensus and identification of novel biomarkers
by: Ow, Ghim Siong, et al.
Published: (2018) -
Adipose-enriched peri-tumoral stroma, in contrast to myofibroblast-enriched stroma, prognosticates poorer survival in breast cancers
by: Lau, Hannah Si Hui, et al.
Published: (2024) -
Germline breast cancer susceptibility genes, tumor characteristics, and survival
by: Ho, Peh Joo, et al.
Published: (2022) -
Multi-center evaluation of artificial intelligent imaging and clinical models for predicting neoadjuvant chemotherapy response in breast cancer
by: Tan, Hong Qi, et al.
Published: (2022)