Application of feature selection algorithms in gene expression data analysis

• Main Author: Wang, Ruiping.
• Other Authors: Mao Kezhi
• Format: Final Year Project
• Language: English
• Published: 2010
• Subjects: DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems; DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition; DRNTU::Engineering::Electrical and electronic engineering
• Online Access: http://hdl.handle.net/10356/38899
• Institution: Nanyang Technological University

Although there are several causes of cancer, scientists have made a major breakthrough in discovering a number of candidate genes that associated with certain cancers. These genes, recognized as biomarkers, can contribute in early cancer diagnosis and prognosis and hence raise the possibility of curative surgery. The recent DNA microarray technology has made it possible for scientists and researchers to get a view of thousands of genes simultaneously. However, microarray data usually contains a huge number of genes (features) and a relatively small number of samples, which makes cancer prediction or classification based on microarray data more challenging. In this report, we consider the problem of applying feature selection techniques to select a small subset of informative biomarkers from DNA microarray data.