Authors:
Keivan Kianmehr
;
Hongchao Zhang
;
Konstantin Nikolov
;
Tansel Özyer
and
Reda Alhajj
Affiliation:
University of Calgary, Canada
Keyword(s):
bioinformatics, data mining, Feature Selection, Neural Networks, Support Vector Machines.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Business Analytics
;
Data Engineering
;
Data Mining
;
Databases and Information Systems Integration
;
Datamining
;
Enterprise Information Systems
;
Health Information Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
Abstract:
Bioinformatics is the science of managing, mining, and interpreting information from biological sequences and structures. In this paper, we discuss two data mining techniques that can be applied in bioinformatics: namely, Neural Networks (NN) and Support Vector Machines (SVM), and their application in gene expression classification. First, we provide description of the two techniques. Then we propose a new method that combines both SVM and NN. Finally, we present the results obtained from our method and the results obtained from SVM alone on a sample dataset.