Title: Mining nutrigenetics patterns related to obesity: use of parallel multifactor dimensionality reduction

Authors: Katerina N. Karayianni; Keith A. Grimaldi; Konstantina S. Nikita; Ioannis K. Valavanis

Addresses: School of Electrical and Computer Engineering, National Technical University of Athens, 9 Iroon Polytechniou Str., 15780 Zografos, Athens, Greece ' School of Electrical and Computer Engineering, National Technical University of Athens, 9 Iroon Polytechniou Str., 15780 Zografos, Athens, Greece ' School of Electrical and Computer Engineering, National Technical University of Athens, 9 Iroon Polytechniou Str., 15780 Zografos, Athens, Greece ' Institute of Biology, Medicinal Chemistry and Biotechnology, National Hellenic Research Foundation, Athens, Greece

Abstract: This paper aims to enlighten the complex etiology beneath obesity by analysing data from a large nutrigenetics study, in which nutritional and genetic factors associated with obesity were recorded for around two thousand individuals. In our previous work, these data have been analysed using artificial neural network methods, which identified optimised subsets of factors to predict one's obesity status. These methods did not reveal though how the selected factors interact with each other in the obtained predictive models. For that reason, parallel Multifactor Dimensionality Reduction (pMDR) was used here to further analyse the pre-selected subsets of nutrigenetic factors. Within pMDR, predictive models using up to eight factors were constructed, further reducing the input dimensionality, while rules describing the interactive effects of the selected factors were derived. In this way, it was possible to identify specific genetic variations and their interactive effects with particular nutritional factors, which are now under further study.

Keywords: data mining; nutrigenetics; obesity; pMDR; multifactor dimensionality reduction; parallel MDR; predictive modelling; genetic variations; single nucleotide polymorphism; SNP; pattern mining; bioinformatics.

DOI: 10.1504/IJBRA.2015.069194

International Journal of Bioinformatics Research and Applications, 2015 Vol.11 No.3, pp.233 - 246

Accepted: 24 Feb 2014
Published online: 05 May 2015 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article