Gene selection for high dimensional data using k-means clustering algorithm and statistical approach

• Main Authors: Ahmad, Farzana Kabir, Yusof, Yuhanis, Othman, Nor Hayati
• Format: Conference or Workshop Item
• Language: English
• Published: 2014
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://repo.uum.edu.my/16491/1/IEEE1.pdf; http://repo.uum.edu.my/16491/; http://doi.org/10.1109/ICCST.2014.7045188
• Institution: Universiti Utara Malaysia

Microarray technology can measure thousands of genes which are useful for biologist to study and classify the cancer cells.However, this high dimensional data consists of large number of genes to be examined in regard of small samples size. Thus, selection of relevant genes is a challenging issue in...