mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling

Table 12

The best predictive genes that give highest classification accuracy for all microarray datasets using mRMR-ABC algorithm.

Datasets	Predictive genes	Accuracy
Colon	Gene115, Gene161, Gene57, Gene70, Gene12, Gene132, Gene84, Gene62, Gene26, Gene155, Gene39, Gene14, Gene1924, Gene148, and Gene21	96.77%
Leukemia1	M31994_at, U07563_cds1_at, Y07604_at, J03925_at, X03484_at, U43522_at, U12622_at, L77864_at, HG3707-HT3922_f_at, D49950_at, HG4011-HT4804_s_at, Y07755_at, M81830_at, and U03090_at	100%
Lung	U77827_at, D49728_at, HG3976-HT4246_at, X77588_s_at, M21535_at, L29433_at, U60115_at, and M14764_at	100%
SRBCT	Gene795, Gene575, Gene423, Gene2025, Gene1090, Gene1611, Gene1389, Gene338, Gene1, and Gene715	100%
Lymphoma	Gene1219X, Gene656X, Gene2075X, Gene3344X, and Gene345X	100%
Leukemia2	Y09615_atD87683_at, U31973_s_at, U68031_at, V00571_rna1_at, L39009_at, U37529_at, U35407_at, X93511_s_at, L15533_rna1_at, X00695_s_at, H46990_at, U47686_s_at, L27624_s_at, S76473_s_at, X16281_at, M37981_at, M89957_at, L05597_at, and X07696_at	100%