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http://www.scirp.org/journal/PaperInformation.aspx?PaperID=16#.VNMxHCzQrzE
http://www.scirp.org/journal/PaperInformation.aspx?PaperID=16#.VNMxHCzQrzE
Affiliation(s)
Department of Mathematics & Computer Science Virginia State University Petersburg, VA 23806, USA.
Department of Computer Science Shippensburg University Shippensburg, PA 17257, USA.
Department of Computer Science Shippensburg University Shippensburg, PA 17257, USA.
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.
Cite this paper
References
Mao, W. and Lee, J. (2008) A Combinatorial Analysis of Genetic Data for Crohn's Disease. Journal of Biomedical Science and Engineering, 1, 52-58. doi: 10.4236/jbise.2008.11008.
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