IntelliGO: a new vector-based semantic similarity measure including annotation origin

BMC Bioinformatics

Methodology Article

Olivier Poch¹  Marie-Dominique Devignes²  Sidahmed Benabderrahmane²  Amedeo Napoli²  Malika Smail-Tabbone² 

[1] L.B.G.I., CNRS UMR7104, IGBMC, 1 rue Laurent Fries, 67404, Illkirch Strasbourg, France;Équipe Orpailleur, Bâtiment B, Campus scientifique, LORIA (CNRS, INRIA, Nancy-Université), 54506, Vandoeuvre-lès-Nancy Cedex, France;

关键词: Gene Ontology;    Similarity Measure;    Semantic Similarity;    KEGG Pathway;    Annotation Term;   

DOI  :  10.1186/1471-2105-11-588

 received in 2010-05-19, accepted in 2010-12-01,  发布年份 2010

来源: Springer

【 摘 要 】

BackgroundThe Gene Ontology (GO) is a well known controlled vocabulary describing the biological process, molecular function and cellular component aspects of gene annotation. It has become a widely used knowledge source in bioinformatics for annotating genes and measuring their semantic similarity. These measures generally involve the GO graph structure, the information content of GO aspects, or a combination of both. However, only a few of the semantic similarity measures described so far can handle GO annotations differently according to their origin (i.e. their evidence codes).ResultsWe present here a new semantic similarity measure called IntelliGO which integrates several complementary properties in a novel vector space model. The coefficients associated with each GO term that annotates a given gene or protein include its information content as well as a customized value for each type of GO evidence code. The generalized cosine similarity measure, used for calculating the dot product between two vectors, has been rigorously adapted to the context of the GO graph. The IntelliGO similarity measure is tested on two benchmark datasets consisting of KEGG pathways and Pfam domains grouped as clans, considering the GO biological process and molecular function terms, respectively, for a total of 683 yeast and human genes and involving more than 67,900 pair-wise comparisons. The ability of the IntelliGO similarity measure to express the biological cohesion of sets of genes compares favourably to four existing similarity measures. For inter-set comparison, it consistently discriminates between distinct sets of genes. Furthermore, the IntelliGO similarity measure allows the influence of weights assigned to evidence codes to be checked. Finally, the results obtained with a complementary reference technique give intermediate but correct correlation values with the sequence similarity, Pfam, and Enzyme classifications when compared to previously published measures.ConclusionsThe IntelliGO similarity measure provides a customizable and comprehensive method for quantifying gene similarity based on GO annotations. It also displays a robust set-discriminating power which suggests it will be useful for functional clustering.AvailabilityAn on-line version of the IntelliGO similarity measure is available at: http://bioinfo.loria.fr/Members/benabdsi/intelligo_project/

【 授权许可】

CC BY   
© Benabderrahmane et al; licensee BioMed Central Ltd. 2010. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.