RNALoc-LM: RNA subcellular localization prediction using pre-trained RNA language model.

ABSTRACT:

Motivation

Accurately predicting RNA subcellular localization is crucial for understanding the cellular functions and regulatory mechanisms of RNAs. Although many computational methods have been developed to predict the subcellular localization of lncRNAs, miRNAs, and circRNAs, very few of them are designed to simultaneously predict the subcellular localization of multiple types of RNAs. In addition, the emergence of pre-trained RNA language model has shown remarkable performance in various bioinformatics tasks, such as structure prediction and functional annotation. Despite these advancements, there remains a significant gap in applying pre-trained RNA language models specifically for predicting RNA subcellular localization.

Results

In this study, we proposed RNALoc-LM, the

SUBMITTER: Zeng M 

PROVIDER: S-EPMC11978386 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature