Gene function prediction in five model eukaryotes exclusively based on gene relative location through machine learning.

ABSTRACT: The function of most genes is unknown. The best results in automated function prediction are obtained with machine learning-based methods that combine multiple data sources, typically sequence derived features, protein structure and interaction data. Even though there is ample evidence showing that a gene's function is not independent of its location, the few available examples of gene function prediction based on gene location rely on sequence identity between genes of different organisms and are thus subjected to the limitations of the relationship between sequence and function. Here we predict thousands of gene functions in five model eukaryotes (Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster, Mus musculus and Homo sapiens) using machine learning models exclus

SUBMITTER: Pazos Obregon F 

PROVIDER: S-EPMC9270439 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature