Identify RNA-associated subcellular localizations based on multi-label learning using Chou's 5-steps rule.

ABSTRACT:

Background

Biological functions of biomolecules rely on the cellular compartments where they are located in cells. Importantly, RNAs are assigned in specific locations of a cell, enabling the cell to implement diverse biochemical processes in the way of concurrency. However, lots of existing RNA subcellular localization classifiers only solve the problem of single-label classification. It is of great practical significance to expand RNA subcellular localization into multi-label classification problem.

Results

In this study, we extract multi-label classification datasets about RNA-associated subcellular localizations on various types of RNAs, and then construct subcellular localization datasets on four RNA categories. In order to study Homo sapiens, we further establish human

SUBMITTER: Wang H 

PROVIDER: S-EPMC7811227 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature