| BMC Genomics | |
| Exploring the key genes and signaling transduction pathways related to the survival time of glioblastoma multiforme patients by a novel survival analysis model | |
| Research | |
| Zhenzhou Yang1  Nan Hu1  Xiaoyu He2  Yuan Xia3  Le Zhang4  Tingting Li5  Chuanwei Yang6  | |
| [1] Cancer Center, Research Institute of Surgery, Daping Hospital, Third Military Medical University, 400042, Chongqing, People’s Republic of China;Chongqing Zhongdi Medical Information Technology Co., Ltd, 401320, Chongqing, People’s Republic of China;College of Computer and Information Science, Southwest University, 400715, Chongqing, People’s Republic of China;College of Computer and Information Science, Southwest University, 400715, Chongqing, People’s Republic of China;College of Mathematics and Statistics, Southwest University, 400715, Chongqing, People’s Republic of China;College of Mathematics and Statistics, Southwest University, 400715, Chongqing, People’s Republic of China;Systems Biology, the University of Texas MD Anderson Cancer Center, Houston, USA;Breast Medical Oncology, the University of Texas MD Anderson Cancer Center, Houston, USA; | |
| 关键词: Least absolute shrinkage and selection operator (Lasso); Sure independence screening (SIS); Cox proportional hazards model (Cox); Glioblastoma multiforme (GBM); Signaling transduction pathway; | |
| DOI : 10.1186/s12864-016-3256-3 | |
| 来源: Springer | |
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【 摘 要 】
BackgroundThis study is to explore the key genes and signaling transduction pathways related to the survival time of glioblastoma multiforme (GBM) patients.ResultsOur results not only showed that mutually explored GBM survival time related genes and signaling transduction pathways are closely related to the GBM, but also demonstrated that our innovated constrained optimization algorithm (CoxSisLasso strategy) are better than the classical methods (CoxLasso and CoxSis strategy).ConclusionWe analyzed why the CoxSisLasso strategy can outperform the existing classical methods and discuss how to extend this research in the distant future.
【 授权许可】
CC BY
© The Author(s). 2017
【 预 览 】
| Files | Size | Format | View |
|---|---|---|---|
| RO202311101707470ZK.pdf | 1452KB | ||
| Fig. 2 | 69KB | Image | |
| Fig. 4 | 1966KB | Image | |
| Fig. 2 | 2010KB | Image | |
| Fig. 6 | 648KB | Image | |
| MediaObjects/40560_2023_693_MOESM3_ESM.docx | 60KB | Other |
【 图 表 】
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