小桶
计算生物学
百科全书
计算机科学
冗余(工程)
鉴定(生物学)
癌变
情报检索
癌症
生物信息学
生物
基因
基因本体论
基因表达
遗传学
操作系统
植物
图书馆学
作者
Fei Yuan,Liwu Lin,Yuhang Zhang,Shaopeng Wang,Yi Cai
标识
DOI:10.1016/j.mbs.2018.08.001
摘要
LncRNAs plays an important role in the regulation of gene expression. Identification of cancer-related lncRNAs GO terms and KEGG pathways is great helpful for revealing cancer-related functional biological processes. Therefore, in this study, we proposed a computational method to identify novel cancer-related lncRNAs GO terms and KEGG pathways. By using existing lncRNA database and Max-relevance Min-redundancy (mRMR) method, GO terms and KEGG pathways were evaluated based on their importance on distinguishing cancer-related and non-cancer-related lncRNAs. Finally, GO terms and KEGG pathways with high importance were presented and analyzed. Our literature reviewing showed that the top 10 ranked GO terms and pathways were really related to interpretable tumorigenesis according to recent publications.
科研通智能强力驱动
Strongly Powered by AbleSci AI