DLRAPom: a hybrid pipeline of Optimized XGBoost-guided integrative multiomics analysis for identifying targetable disease-related lncRNA-miRNA-mRNA regulatory axes.

ABSTRACT: The lack of a reliable and easy-to-operate screening pipeline for disease-related noncoding RNA regulatory axis is a problem that needs to be solved urgently. To address this, we designed a hybrid pipeline, disease-related lncRNA-miRNA-mRNA regulatory axis prediction from multiomics (DLRAPom), to identify risk biomarkers and disease-related lncRNA-miRNA-mRNA regulatory axes by adding a novel machine learning model on the basis of conventional analysis and combining experimental validation. The pipeline consists of four parts, including selecting hub biomarkers by conventional bioinformatics analysis, discovering the most essential protein-coding biomarkers by a novel machine learning model, extracting the key lncRNA-miRNA-mRNA axis and validating experimentally. Our study is the first one

SUBMITTER: Shen C 

PROVIDER: S-EPMC8921741 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature