title: Hierarchical gene selection and genetic fuzzy system for cancer microarray data classification.
abstract: This paper introduces a novel approach to gene selection based on a substantial modification of analytic hierarchy process (AHP). The modified AHP systematically integrates outcomes of individual filter methods to select the most informative genes for microarray classification. Five individual ranking methods including t-test, entropy, receiver operating characteristic (ROC) curve, Wilcoxon and signal to noise ratio are employed to rank genes. These ranked genes are then considered as inputs for the modified AHP. Additionally, a method that uses fuzzy standard additive model (FSAM) for cancer classification based on genes selected by AHP is also proposed in this paper. Traditional FSAM learning is a hybrid process comprising unsupervised structure learning and supervised parameter tuning. Genetic algorithm (GA) is incorporated in-between unsupervised and supervised training to optimize the number of fuzzy rules. The integration of GA enables FSAM to deal with the high-dimensional-low-sample nature of microarray data and thus enhance the efficiency of the classification. Experiments are carried out on numerous microarray datasets. Results demonstrate the performance dominance of the AHP-based gene selection against the single ranking methods. Furthermore, the combination of AHP-FSAM shows a great accuracy in microarray data classification compared to various competing classifiers. The proposed approach therefore is useful for medical practitioners and clinicians as a decision support system that can be implemented in the real medical practice.
authors.affiliation: Centre for Intelligent Systems Research (CISR), Deakin University, Geelong Waurn Ponds Campus, Victoria, 3216, Australia.
authors.forename: Thanh
authors.initials: T
authors.lastname: Nguyen
authors.affiliation: Centre for Intelligent Systems Research (CISR), Deakin University, Geelong Waurn Ponds Campus, Victoria, 3216, Australia.
authors.forename: Abbas
authors.initials: A
authors.lastname: Khosravi
authors.affiliation: Centre for Intelligent Systems Research (CISR), Deakin University, Geelong Waurn Ponds Campus, Victoria, 3216, Australia.
authors.forename: Douglas
authors.initials: D
authors.lastname: Creighton
authors.affiliation: Centre for Intelligent Systems Research (CISR), Deakin University, Geelong Waurn Ponds Campus, Victoria, 3216, Australia.
authors.forename: Saeid
authors.initials: S
authors.lastname: Nahavandi
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods; D004273:DNA, Neoplasm / Q000235:genetics; D003627:Data Interpretation, Statistical; D030541:Databases, Genetic / Q000706:statistics & numerical data; D020000:Decision Support Systems, Clinical; D017143:Fuzzy Logic; D020869:Gene Expression Profiling / Q000379:methods* / Q000706:statistics & numerical data; D006801:Humans; D007938:Leukemia / Q000235:genetics; D016403:Lymphoma, Large B-Cell, Diffuse / Q000235:genetics; D008957:Models, Genetic; D015233:Models, Statistical; D009369:Neoplasms / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods* / Q000706:statistics & numerical data; D012372:ROC Curve; D000069553:Supervised Machine Learning; D000069558:Unsupervised Machine Learning
chemical_list: D004273:DNA, Neoplasm
references.citation: Blood. 2005 Mar 1;105(5):1851-61
references.pmid: 15550490
references.citation: PLoS One. 2010;5(12):e14305
references.pmid: 21200431
references.citation: IEEE/ACM Trans Comput Biol Bioinform. 2012 Nov-Dec;9(6):1831-6
references.pmid: 23221091
references.citation: Bioinformatics. 2003 Jan 22;19(2):185-93
references.pmid: 12538238
references.citation: IEEE/ACM Trans Comput Biol Bioinform. 2012 Nov-Dec;9(6):1649-62
references.pmid: 22868679
references.citation: Nat Med. 2001 Jun;7(6):673-9
references.pmid: 11385503
references.citation: PLoS One. 2013;8(8):e69873
references.pmid: 23936357
references.citation: Neural Netw. 1999 Jan;12(1):145-151
references.pmid: 12662723
references.citation: Bioinformatics. 2005 May 15;21(10):2394-402
references.pmid: 15713736
references.citation: Brief Bioinform. 2013 Jul;14(4):402-10
references.pmid: 22988257
references.citation: IEEE/ACM Trans Comput Biol Bioinform. 2010 Jan-Mar;7(1):108-17
references.pmid: 20150673
references.citation: BMC Bioinformatics. 2014;15:31
references.pmid: 24475928
references.citation: BMC Bioinformatics. 2011;12:391
references.pmid: 21982331
references.citation: J Bioinform Comput Biol. 2005 Apr;3(2):185-205
references.pmid: 15852500
references.citation: PLoS One. 2010;5(10):e13696
references.pmid: 21060876
references.citation: IEEE Trans Syst Man Cybern B Cybern. 1996;26(4):542-60
references.pmid: 18263053
references.citation: J Biomed Inform. 2010 Feb;43(1):81-7
references.pmid: 19699316
references.citation: Science. 1999 Oct 15;286(5439):531-7
references.pmid: 10521349