Classifying Virus Strain Using a Machine Learning Model Based on Subcellular Localization Data

Abstract

The topic of mRNA subcellular localization is very useful for further study. And one of the most significant reasons to study deep into this topic is to study mRNA functions. The location of the particular mRNA is very important, as well as its function. Localization of mRNA can be used for a variety of reasons. Therefore, several tools were developed to predict mRNA localization. Due to the various importance and functions of subcellular localization, further studies and research have been given significant attention by the researchers. Among all of the tools developed, some notable differences between those existing machine learning models are the methods implemented within the models. These methods give huge impacts on the outcomes of the prediction model. In this paper, the research focuses on analyzing the methodology and performance of mRNA subcellular localization prediction models.