High-throughput experiments are becoming standard techniques used in molecular biology. The necessity to extrapolate knowledge from this huge volume of data (such as regulative molules and gene activities) motivated the recent development of several gene similarity measures that operate on the Gene Ontology (GO).
However, the main goal in the design of the GO is the definition of a structured vocabulary for genes description. In contrast, functional similarity measures would benefit from a structure purposely built to emphasizes genes involved in the same biological context. As a consequence such measures often find it difficult to fully exploit the information in the GO.

For this purpouse we introduce a technique for reorganizing the GO so to emphasize regulative information and to provide better structure for gene functional analysis by means of similarity measures. We call the new structure Restructured GO (RGO).

The RGO is a weighted direct acyclic graph.
It is composed by three interconnected sub-ontologies representing (as in the GO) the three aspects of genes/proteins functions: the Biological Process (RGO:BP) sub-ontology describes the molecular events at the gene/protein level; the Molecular Function (RGO:MF) sub-ontology indicates the biochemical activities of a gene product; the Cellular Component (RGO:CC) sub-ontology details the cellular places where the gene product is active.

The RGO improves over the existing GO since:

RGO is currently based on gene ontology database published by the gene ontology consortium in March 2010.


Download the RGO.

A web interface to browse the RGO structure and annotations, and a tool to compute a functional similarity measure that exploits the RGO improvements will be published shortly.


Visconti A., Esposito R., and Cordero F., Restructuring the Gene Ontology to Emphasize Regulative Pathways and to Improve Gene Similarity Queries, Int. J. Computational Biology and Drug Design, Vol. 4, No. 3, 2011, Inderscience Publishers, pag 220-238, ISSN 1756-0764

Visconti A., Cordero F., Botta M. and Calogero R.A., Gene Ontology rewritten for computing gene functional similarity In Proceedings of the Fourth International Conferences on Complex, Intelligent and Software Intensive Systems, February 15-18 2010, IEEE Computer Society Press, pag 694-699 ISBN 978-0-7695-3967-6


Esposito R., Visconti A.