Annotation-based feature extraction from sets of SBML models.

ABSTRACT:

Background

Model repositories such as BioModels Database provide computational models of biological systems for the scientific community. These models contain rich semantic annotations that link model entities to concepts in well-established bio-ontologies such as Gene Ontology. Consequently, thematically similar models are likely to share similar annotations. Based on this assumption, we argue that semantic annotations are a suitable tool to characterize sets of models. These characteristics improve model classification, allow to identify additional features for model retrieval tasks, and enable the comparison of sets of models.

Results

In this paper we discuss four methods for annotation-based feature extraction from model sets. We tested all methods on sets of models in S

SUBMITTER: Alm R 

PROVIDER: S-EPMC4405863 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature