Literature DB >> 22364779

Extracting plants core genes responding to abiotic stresses by penalized matrix decomposition.

Jin-Xing Liu1, Chun-Hou Zheng, Yong Xu.   

Abstract

Sparse methods have a significant advantage to reduce the complexity of genes expression data and to make them more comprehensible and interpretable. In this paper, based on penalized matrix decomposition (PMD), a novel approach is proposed to extract plants core genes, i.e., the characteristic gene set, responding to abiotic stresses. Core genes can capture the changes of the samples. In other words, the features of samples can be caught by the core genes. The experimental results show that the proposed PMD-based method is efficient to extract the core genes closely related to the abiotic stresses.
Copyright © 2012 Elsevier Ltd. All rights reserved.

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Year:  2012        PMID: 22364779     DOI: 10.1016/j.compbiomed.2012.02.002

Source DB:  PubMed          Journal:  Comput Biol Med        ISSN: 0010-4825            Impact factor:   4.589


  6 in total

1.  An NMF-L2,1-Norm Constraint Method for Characteristic Gene Selection.

Authors:  Dong Wang; Jin-Xing Liu; Ying-Lian Gao; Jiguo Yu; Chun-Hou Zheng; Yong Xu
Journal:  PLoS One       Date:  2016-07-18       Impact factor: 3.240

2.  Characteristic gene selection via weighting principal components by singular values.

Authors:  Jin-Xing Liu; Yong Xu; Chun-Hou Zheng; Yi Wang; Jing-Yu Yang
Journal:  PLoS One       Date:  2012-07-10       Impact factor: 3.240

3.  A P-Norm Robust Feature Extraction Method for Identifying Differentially Expressed Genes.

Authors:  Jian Liu; Jin-Xing Liu; Ying-Lian Gao; Xiang-Zhen Kong; Xue-Song Wang; Dong Wang
Journal:  PLoS One       Date:  2015-07-22       Impact factor: 3.240

4.  A class-information-based penalized matrix decomposition for identifying plants core genes responding to abiotic stresses.

Authors:  Jin-Xing Liu; Jian Liu; Ying-Lian Gao; Jian-Xun Mi; Chun-Xia Ma; Dong Wang
Journal:  PLoS One       Date:  2014-09-02       Impact factor: 3.240

5.  An Optimal Mean Based Block Robust Feature Extraction Method to Identify Colorectal Cancer Genes with Integrated Data.

Authors:  Jian Liu; Yuhu Cheng; Xuesong Wang; Lin Zhang; Hui Liu
Journal:  Sci Rep       Date:  2017-08-17       Impact factor: 4.379

6.  Robust PCA based method for discovering differentially expressed genes.

Authors:  Jin-Xing Liu; Yu-Tian Wang; Chun-Hou Zheng; Wen Sha; Jian-Xun Mi; Yong Xu
Journal:  BMC Bioinformatics       Date:  2013-05-09       Impact factor: 3.169

  6 in total

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