RPI-SE: a stacking ensemble learning framework for ncRNA-protein interactions prediction using sequence information.

ABSTRACT: BACKGROUND:The interactions between non-coding RNAs (ncRNA) and proteins play an essential role in many biological processes. Several high-throughput experimental methods have been applied to detect ncRNA-protein interactions. However, these methods are time-consuming and expensive. Accurate and efficient computational methods can assist and accelerate the study of ncRNA-protein interactions. RESULTS:In this work, we develop a stacking ensemble computational framework, RPI-SE, for effectively predicting ncRNA-protein interactions. More specifically, to fully exploit protein and RNA sequence feature, Position Weight Matrix combined with Legendre Moments is applied to obtain protein evolutionary information. Meanwhile, k-mer sparse matrix is employed to extract efficient feature of ncRNA seq

SUBMITTER: Yi HC 

PROVIDER: S-EPMC7029608 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature