Title:

OS6-2 Adaptive Polynomial Regression and Its Application to Gene Selection of Rat Liver Regeneration

Publication: ICAROB2016
Volume: 21
Pages: 320-323
ISSN: 2188-7829
DOI: 10.5954/ICAROB.2016.OS6-2
Author(s): Juntao Li, Yimin Cao, Xiaoyu Wang, Cunshuan Xu
Publication Date: January 29, 2016
Keywords: multi-class classification, polynomial regression, gene selection, rat liver regeneration
Abstract: To deal with multi-class classification problem for gene expression data, this paper proposed an adaptive polynomial regression by incorporating multi-class adaptive elastic net penalty into polynomial likelihood loss. The adaptive polynomial regression was proved to adaptively select relevant genes in groups in performing multi-class classification. The proposed method was successfully applied to gene expression data for rat liver regeneration and the relevant genes were selected. The pathway relationships among the selected genes were also provided to verify their biological rationality.
PDF File: https://alife-robotics.co.jp/members2016/icarob/data/papers/OS/OS6-2.pdf
Copyright: © The authors.
This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited.
See for details: https://creativecommons.org/licenses/by-nc/4.0/

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