Ontology highlight
ABSTRACT:
SUBMITTER: Fabris F
PROVIDER: S-EPMC6041990 | biostudies-literature | 2018 Jul
REPOSITORIES: biostudies-literature
Fabris Fabio F Doherty Aoife A Palmer Daniel D de Magalhães João Pedro JP Freitas Alex A AA
Bioinformatics (Oxford, England) 20180701 14
<h4>Motivation</h4>This work uses the Random Forest (RF) classification algorithm to predict if a gene is over-expressed, under-expressed or has no change in expression with age in the brain. RFs have high predictive power, and RF models can be interpreted using a feature (variable) importance measure. However, current feature importance measures evaluate a feature as a whole (all feature values). We show that, for a popular type of biological data (Gene Ontology-based), usually only one value o ...[more]