Gene ontology fuzzy-enrichment analysis to investigate drug mode-of-action

Author

Iorio, Francesco ; Murino, Loredana ; Di Bernardo, Diego ; Raiconi, Giancarlo ; Tagliaferri, Roberto

Author_Institution

Dept. of Math. & Comput. Sci. (DMI), Univ. of Salerno, Fisciano, Italy

fYear

2010

fDate

18-23 July 2010

Firstpage

1

Lastpage

7

Abstract

We investigated the possibility of gaining information on the mode of action of a set of compounds by means of Gene Ontology (GO) enrichment analysis. To this aim, we developed a new method, based on fuzzy-sets, which is able to compute sets of genes that are consistently differentially expressed when treating cells with the analyzed compounds. Then a Gene Ontology enrichment analysis is performed on these sets. The method has been tested on several different groups of drugs, whose similarity in mode of action has been predicted by a gene-expression based, unsupervised, approach and verified by searching literature. The obtained results show that GO terms that are overrepresented in these fuzzy sets provide a quick and "easy-tointerpret" view of the mode of action of the analyzed drugs.

Keywords

drugs; fuzzy set theory; genetics; medical computing; ontologies (artificial intelligence); drug mode-of-action; easy-to-interpret; enrichment analysis; fuzzy-sets; gene ontology fuzzy-enrichment analysis; Biological processes; Clustering algorithms; Communities; Compounds; Drugs; Inhibitors; Proteins;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks (IJCNN), The 2010 International Joint Conference on

Conference_Location

Barcelona

ISSN

1098-7576

Print_ISBN

978-1-4244-6916-1

Type

conf

DOI

10.1109/IJCNN.2010.5596585

Filename

5596585