- Full (HTML) - Full (PDF) - Supplemental Material - Related EHP Articles - PubMed:Related Articles - PubMed:Citation - Cited in PMC - Purchase This Issue

Charles D. Johnson,^1,2 Yoganand Balagurunathan,³ Mahlet G. Tadesse,⁴ M. Hadi Falahatpisheh,^1,2 Marcel Brun,^1,3 Mary K. Walker,⁵ Edward R. Dougherty,³ and Kenneth S. Ramos^1,2

¹Department of Biochemistry and Molecular Biology and Center for Genetics and Molecular Medicine, University of Louisville, Louisville, Kentucky, USA; Departments of ²Veterinary Physiology and Pharmacology, ³Electrical Engineering, and ⁴Statistics, Texas A&M University, College Station, Texas, USA; ⁵Department of Pharmacology and Toxicology, University of New Mexico, Albuquerque, New Mexico, USA

Abstract
The co-expression of genes coupled to additive probabilistic relationships was used to identify gene sets predictive of the complex biological interactions regulated by ligands of the aryl hydrocarbon receptor (Ahr) . To maximize the number of possible gene-gene combinations, data sets from murine embryonic kidney, fetal heart, and vascular smooth muscle cells challenged in vitro with ligands of the Ahr were used to create predictor/training data sets. Biologically relevant gene predictor sets were calculated for Ahr, cytochrome P450 1B1, insulin-like growth factor-binding protein-5, lysyl oxidase, and osteopontin. Transcript levels were categorized into ternary expressions and target genes selected from the data set and tested for all possible combinations using three gene sets as predictors of transitional level. The goodness of prediction for each set was quantified using a multivariate nonlinear coefficient of determination. Evidence is presented that predictor gene combinations can be effectively used to resolve gene-gene interactions regulated by Ahr ligands. Key words: aryl hydrocarbon receptor, bioinformatics, gene networks, genomics. Environ Health Perspect 112:403-412 (2004) . doi:10.1289/txg.6758 available via http://dx.doi.org/ [Online 14 January 2004]

Address correspondence to K.S. Ramos, Department of Biochemistry and Molecular Biology, University of Louisville Health Sciences Center, Louisville, KY 40292 USA. Telephone: (502) 852-5217. Fax: (502) 852-6222. E-mail: kenneth.ramos@louisville.edu

*The online version of this article (available at http://www.ehponline.org) contains Supplemental Material.

This research was supported by National Institutes of Health grants ES04849, ES09106, ES07273 to K.S.R and ES09804 and ES012072 to M.K.W. C.D.J was supported by National Research Service Award (NSRA) ES012117, M.G.T by National Cancer Institute CA90301, and M.H.F. by NRSA ES012542.

The authors declare they have no competing financial interests.

Received 23 September 2003 ; accepted 14 January 2004.

The full version of this article is available for free in HTML or PDF formats.