Related Experiment Video
Updated: Jun 15, 2026

Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
Published on: January 31, 2014
Modeling sample variables with an Experimental Factor Ontology
James Malone1, Ele Holloway, Tomasz Adamusiak
1Microarray Informatics Team, EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK. malone@ebi.ac.uk
Motivation:
Describing biological sample variables with ontologies is complex due to the cross-domain nature of experiments. Ontologies provide annotation solutions; however, for cross-domain investigations, multiple ontologies are needed to represent the data. These are subject to rapid change, are often not interoperable and present complexities that are a barrier to biological resource users.
Results:
We present the Experimental Factor Ontology, designed to meet cross-domain, application focused use cases for gene expression data. We describe our methodology and open source tools used to create the ontology. These include tools for creating ontology mappings, ontology views, detecting ontology changes and using ontologies in interfaces to enhance querying. The application of reference ontologies to data is a key problem, and this work presents guidelines on how community ontologies can be presented in an application ontology in a data-driven way.
Availability:
http://www.ebi.ac.uk/efo.
Related Concept Videos
Typical Model Studies
Experimental Designs
Mechanistic Models: Compartment Models in Individual and Population Analysis
Modeling and Similitude
Factorial Design
Data Collection by Experiments
An example of the experimental method is a public clinical trial...
