Machine Learning Based Network Analysis Determined Clinically Relevant miRNAs in Breast Cancer.

ABSTRACT:

Background and aims

MicroRNAs (miRNAs) have been shown to play important roles in many cancers, including breast cancer. The majority of previous studies employed network analysis to identify key miRNAs in cancer progression. However, most of dysregulated miRNA networks were constructed based on the expression variation of miRNAs and target genes.

Methods

The relations between miRNAs and target genes were computed by Spearman correlation separately in breast cancer and normal breast samples. We calculated dysregulated scores based on the dysregulation of miRNA-mRNA regulatory relations. A dysregulated miRNA target network (DMTN) was constructed from the miRNA-mRNA pairs with significant dysregulated scores. SVM classifier was employed to predict breast cancer risk miRNAs fro

SUBMITTER: Qiu M 

PROVIDER: S-EPMC7689188 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature