Pseudo2GO: A Graph-Based Deep Learning Method for Pseudogene Function Prediction by Borrowing Information From Coding Genes.

ABSTRACT: Pseudogenes are indicating more and more functional potentials recently, though historically were regarded as relics of evolution. Computational methods for predicting pseudogene functions on Gene Ontology is important for directing experimental discovery. However, no pseudogene-specific computational methods have been proposed to directly predict their Gene Ontology (GO) terms. The biggest challenge for pseudogene function prediction is the lack of enough features and functional annotations, making training a predictive model difficult. Considering the close functional similarity between pseudogenes and their parent coding genes that share great amount of DNA sequence, as well as that coding genes have rich annotations, we aim to predict pseudogene functions by borrowing information from

SUBMITTER: Fan K 

PROVIDER: S-EPMC7461887 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature