| Literature DB >> 30378074 |
Xu Zhang1, Tsui-Ting Ho2.
Abstract
Long noncoding RNAs (lncRNAs) have been shown to play crucial roles in cancer biology. With the help of computational analysis illustrated here, the joint effects of lncRNAs and clinical variables can be quantified in a Cox model on cancer recurrence. Of importance, the predictive accuracy was then validated with the prognostic scores computed based on the suggested model. Further investigation of these potential lncRNAs would provide useful insights following the study of the mechanisms underlying the differential expression of these lncRNAs in association with and possibly contributing to cancer recurrence. Ultimately, the expanding knowledge of the function of lncRNAs curated by computational analysis will suggest new targets for cancer treatment.Entities:
Keywords: Cancer; Cox model; Experimental validation; Lasso method; Model validation; lncRNA
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Year: 2019 PMID: 30378074 DOI: 10.1007/978-1-4939-8868-6_8
Source DB: PubMed Journal: Methods Mol Biol ISSN: 1064-3745