Using deep neural networks and LASSO regression to predict miRNA expression changes based on mRNA data.

ABSTRACT:

Introduction

Since the rise of molecular high-throughput technologies, many diseases are now studied on multiple omics layers in parallel. Understanding the interplay between microRNAs (miRNA) and their target mRNAs is important to understand the molecular level of diseases. While much public data from mRNA experiments are available for many diseases, few paired datasets with both miRNA and mRNA expression profiles are available. This study aimed to assess the possibility of predicting miRNA expression data based on mRNA expression data, serving as a proof of principle that such cross-omics predictions are feasible. Furthermore, current research relies on target databases where information about miRNA-target relationships is provided based on experimental and computational studies.

SUBMITTER: Boge FL 

PROVIDER: S-EPMC12279838 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature