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Gene Expression Data Using Extreme Learning Machine

V. Sivaraj, Dr. S. Sukumaran

Abstract


The aim of this work is to develop a new technique for medical classification problem. In diagnosing cancer, multicategory classification of cancer plays a very significant role. Nowadays, number of cancer suffering is increasing, so effective technique is required. In this work, an Extreme Learning Machine is integrated with the Successive Feature Selection technique for better classification in cancer. The extreme learning machine will rectify the problems such as improper learning rate, local minima, and low speed. This new method is evaluated for using accuracy and execution time and proves that the proposed method is very effective.

Keywords


Cancer Classification, Successive Feature Selection, Extreme Learning Machine, Gene Expression Data

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References


Lovén J, Orlando DA, Sigova AA, Lin CY, Rahl PB, Burge CB, Levens DL, Lee TI, Young RA. Revisiting global gene expression analysis. Cell. 2012 Oct 26; 151(3):476-82.

Rapaport F, Khanin R, Liang Y, Pirun M, Krek A, Zumbo P, Mason CE, Socci ND, Betel D. Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data. Genome Biol. 2013 Sep 10;14(9):R95.

Piccaluga PP, De Falco G, Kustagi M, Gazzola A, Agostinelli C, Tripodo C, Leucci E, Onnis A, Astolfi A, Sapienza MR, Bellan C. Gene expression analysis uncovers similarity and differences among Burkitt lymphoma subtypes. Blood. 2011 Mar 31; 117(13):3596-608.

Wang KC, Yang YW, Liu B, Sanyal A, Corces-Zimmerman R, Chen Y, Lajoie BR, Protacio A, Flynn RA, Gupta RA, Wysocka J. A long noncoding RNA maintains active chromatin to coordinate homeotic gene expression. Nature. 2011 Apr 7;472(7341):120-4.

Berry SM, Alarid ET, Beebe DJ. One-step purification of nucleic acid for gene expression analysis via Immiscible Filtration Assisted by Surface Tension (IFAST). Lab on a chip. 2011;11(10):1747-53.

Kulkarni MM. Digital multiplexed gene expression analysis using the NanoString nCounter system. Current Protocols in Molecular Biology. 2011 Apr 1:25B-10.

Merryweather-Clarke AT, Atzberger A, Soneji S, Gray N, Clark K, Waugh C, McGowan SJ, Taylor S, Nandi AK, Wood WG, Roberts DJ. Global gene expression analysis of human erythroid progenitors. Blood. 2011 Mar 31;117(13):e96-108.

Saraswathi S, Sundaram S, Sundararajan N, Zimmermann M, Nilsen-Hamilton M. ICGA-PSO-ELM approach for accurate multiclass cancer classification resulting in reduced gene sets in which genes encoding secreted proteins are highly represented. Computational Biology and Bioinformatics, IEEE/ACM Transactions on. 2011 Mar;8(2):452-63.

Dinkel H, Michael S, Weatheritt RJ, Davey NE, Van Roey K, Altenberg B, Toedt G, Uyar B, Seiler M, Budd A, Jödicke L. ELM—the database of eukaryotic linear motifs. Nucleic acids research. 2011 Nov 21:gkr1064.

Babu GS, Suresh S. Parkinson’s disease prediction using gene expression–A projection based learning meta-cognitive neural classifier approach. Expert Systems with Applications. 2013 Apr 30; 40(5):1519-29.

Huang GB, Zhou H, Ding X, Zhang R. Extreme learning machine for regression and multiclass classification. Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on. 2012 Apr;42(2):513-29.

Cao J, Xiong L. Protein sequence classification with improved extreme learning machine algorithms. BioMed research international. 2014 Mar 30; 2014.

Deepa SN, Devi BA. A survey on artificial intelligence approaches for medical image classification. Indian Journal of Science and Technology. 2011 Nov 1;4(11):1583-95.

Zainuddin Z, Ong P. Reliable multiclass cancer classification of microarray gene expression profiles using an improved wavelet neural network. Expert Systems with Applications. 2011 Oct 31; 38(11):13711-22.

Wang SJ, Chen HL, Yan WJ, Chen YH, Fu X. Face recognition and micro-expression recognition based on discriminant tensor subspace analysis plus extreme learning machine. Neural processing letters. 2014 Feb 1; 39(1):25-43.


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