A Deep Learning Model to Predict the ncRNA-Protein Interactions Based on Sequences Information Only.

ABSTRACT: Noncoding RNAs (ncRNAs) play significant roles in multiple fundamental biological processes, in particular, ncRNAs interactions provide valuable insights into protein synthesis, controlling gene expression, RNA processing, regulation of localization, etc. The dysregulation of ncRNA interaction may cause severe diseases including cancer. Therefore, developing computational methods for investigating ncRNA-protein interaction has become a problem of interest for researchers. In this study, we proposed a novel deep learning (DL) model named RPI-SDA-XGBoost for predicting the interaction between ncRNA and proteins. We utilized the 3-mer conjoint triad feature (CTF) to encode the protein sequence, and the 4-mer frequency to encode the RNA sequence, resulting in the extraction of a total of 599-d

SUBMITTER: Sewailem MF 

PROVIDER: S-EPMC12602996 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature