A Combinatorial Analysis of Genetic Data for Crohn's Disease

Weidong Mao, Jeonghwa Lee

Department of Computer Science Shippensburg University Shippensburg, PA 17257, USA.
Department of Mathematics & Computer Science Virginia State University Petersburg, VA 23806, USA.

DOI: 10.4236/jbise.2008.11008                

Abstract

The Both environmental and genetic factors have roles in the development of some diseases. Complex diseases, such as Crohn's disease or Type II diabetes, are caused by a combination of environmental factors and mutations in multiple genes. Patients who have been diagnosed with such diseases cannot easily be treated. However, many diseases can be avoided if people at high risk change their living style, one example being their diet. But how can we tell their susceptibility to diseases before symptoms are found and help them make informed decisions about their health? With the development of DNA microarray technique, it is possible to access the human genetic information related to specific diseases. This paper uses a combinatorial method to analyze the genetic data for Crohn's disease and search disease-associated factors for given case/control samples. An optimum random forest based method has been applied to publicly available genotype data on Crohn's disease for association study and achieved a promising result.

Keywords

genetic factor, Crohn’s disease, random forest

Conflicts of Interest

The authors declare no conflicts of interest.

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