Discovering functional impacts of miRNAs in cancers using a causal deep learning model.

Journal: BMC medical genomics
Published Date:

Abstract

BACKGROUND: Micro-RNAs (miRNAs) play a significant role in regulating gene expression under physiological and pathological conditions such as cancers. However, it remains a challenging problem to discover the target messenger RNAs (mRNAs) of a miRNA in a data driven fashion. On one hand, sequence-based methods for predicting miRNA targets tend to make too many false positive calls. On the other hand, analyzing expression correlation between miRNAs and mRNAs cannot establish whether relationship between a pair of correlated miRNA and mRNA is causal.

Authors

  • Lujia Chen
    Department of Biomedical Informatics, University of Pittsburgh, 5607 Baum Blvd, 15237, Pittsburgh, PA, USA. luc17@pitt.edu.
  • Xinghua Lu
    Dept. Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, USA.