Hybrid Binary Imperialist Competition Algorithm and Tabu Search Approach for Feature Selection Using Gene Expression Data

Table 1

Cancer-related human gene microarray datasets used in this study.

Dataset name	Description
9_Tumors	Oligonucleotide microarray gene expression profiles for the chemosensitivity profiles of 232 chemical compounds
11_Tumors	Transcript profiles of 11 common human tumors for carcinomas of the prostate, breast, colorectum, lung, liver, gastroesophagus, pancreas, ovary, kidney, and bladder/ureter
Brain_Tumor 1	DNA microarray gene expression profiles derived from 99 patient samples. The medulloblastomas included primitive neuroectodermal tumors, atypical teratoid/rhabdoid tumors, malignant gliomas, and the medulloblastomas activated by the sonic hedgehog pathway
Brain_Tumor 2	Transcript profiles of four malignant gliomas, including classic glioblastoma, nonclassic glioblastoma, classic oligodendroglioma, and nonclassic oligodendroglioma
Leukemia 1	DNA microarray gene expression profiles of acute myelogenous leukemia (AML) and acute lymphoblastic leukemia (ALL) of B-cell and T-cell
Leukemia 2	Gene expression profiles of a chromosomal translocation to distinguish mixed-lineage leukemia, ALL, and AML
Lung_Cancer	Oligonucleotide microarray transcript profiles of 203 specimens, including lung adenocarcinomas, squamous cell lung carcinomas, pulmonary carcinomas, small-cell lung carcinomas, and normal lung tissue
SRBCT	cDNA microarray gene expression profiles of small, round blue cell tumors, which include neuroblastoma, rhabdomyosarcoma, non-Hodgkin’s lymphoma, and the Ewing family of tumors
Prostate_Tumor	cDNA microarray gene expression profiles of prostate tumors. Based on MUC1 and AZGP1 gene expression, the prostate cancer can be distinguished as a subtype associated with an elevated risk of recurrence or with a decreased risk of recurrence
DLBCL	DNA microarray gene expression profiles of DLBCL, in which the DLBCL can be identified as cured versus fatal or refractory disease