GeneRank-based partly adaptive group-penalised multinomial regression for microarray classification
by Juntao Li; Wenpeng Dong
International Journal of Data Mining and Bioinformatics (IJDMB), Vol. 16, No. 3, 2016

Abstract: This paper proposes a partly adaptive group-penalised multinomial regression for gene selection. Weights with biological significance are constructed by combing the gene expression information with gene ontology network via GeneRank. By introducing the weights into group lasso penalty, the partly adaptive group-penalised multinomial regression is proposed. Two algorithms for fitting the proposed model are presented on the base of blockwise descent. Experimental results on gene expression data of yeast diauxic shift demonstrate that the proposed method can select the stable genes and achieve the better classification performance.

Online publication date: Thu, 01-Dec-2016

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