AUTHOR=Zhao Yingwen , Wang Jun , Chen Jian , Zhang Xiangliang , Guo Maozu , Yu Guoxian 

TITLE=A Literature Review of Gene Function Prediction by Modeling Gene Ontology

JOURNAL=Frontiers in Genetics

VOLUME=Volume 11 - 2020

YEAR=2020

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2020.00400

DOI=10.3389/fgene.2020.00400

ISSN=1664-8021

ABSTRACT=Annotating the functional properties of gene products (i.e., RNAs and proteins) is a fundamental task in biology. Gene Ontology (GO)  has been developed to describe the functional properties of gene products across species in a unified ontology, and to facilitate the computational gene function prediction. GO is routinely updated with the accumulation of biological knowledge, serves as the golden standard and knowledge source in functional genomics. A large number of function prediction methods making different usages of GO have been proposed. But there is  no literature overview to summarize these methods and the future efforts from the perspective of GO. To bridge this gap, we try to
provide a timely review on this direction with emphasis on recent solutions. We first introduce the conventions of GO and the widely-adopted evaluation metrics for gene function prediction. Next, we summarize the progress of gene function prediction based on GO from different perspectives, such as the usage of hierarchical/flat inter-relationships between GO terms, the compression of massive GO terms, semantic similarity quantification and analysis. We conclude that although many efforts have been devoted to harness GO from different perspectives and gained an improved performance, there still have largely overlooked but important topics for future research.