A machine learning framework that integrates multi-omics data predicts cancer-related LncRNAs.

ABSTRACT:

Background

LncRNAs (Long non-coding RNAs) are a type of non-coding RNA molecule with transcript length longer than 200 nucleotides. LncRNA has been novel candidate biomarkers in cancer diagnosis and prognosis. However, it is difficult to discover the true association mechanism between lncRNAs and complex diseases. The unprecedented enrichment of multi-omics data and the rapid development of machine learning technology provide us with the opportunity to design a machine learning framework to study the relationship between lncRNAs and complex diseases.

Results

In this article, we proposed a new machine learning approach, namely LGDLDA (LncRNA-Gene-Disease association networks based LncRNA-Disease Association prediction), for disease-related lncRNAs association prediction based

SUBMITTER: Yuan L 

PROVIDER: S-EPMC8210375 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature