Scholarly Works @ SHSU

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  • Supervised learning-based tagSNP selection for genome-wide disease classifications 

    Liu, Qingzhong; Sung, Andrew H.; Chen, Zhongxue; Yang, Mary Qu; Huang, Xudong; Yang, Jack (BIomed Central, 2007-07-25)
    Comprehensive evaluation of common genetic variations through association of single nucleotide polymorphisms (SNPs) with complex human diseases on the genome-wide scale is an active area in human genome research. One of ...

  • Independent component analysis of Alzheimer's DNA microarray gene expression data 

    Liu, Qingzhong; Chen, Zhongxue; Vanderburg, Charles R; Rogers, Jack T.; Huang, Xudong; Mou, Xiaoyang (Biomed Central, 2009-01-28)
    Gene microarray technology is an effective tool to investigate the simultaneous activity of multiple cellular pathways from hundreds to thousands of genes. However, because data in the colossal amounts generated by DNA ...

  • Comparison of feature selection and classification for MALDI-MS data 

    Liu, Qingzhong; Sung, Andrew H.; Chen, Zhongxue; Yang, Jack Y; Qiao, Mengyu; Yang, Mary Qu; Huang, Xudong; Deng, Youping (BMC Genomics, 2009-07-07)
    In the classification of Mass Spectrometry (MS) proteomics data, peak detection, feature selection, and learning classifiers are critical to classification accuracy. To better understand which methods are more accurate ...

  • Feature Selection and Classification of MAQC-II Breast Cancer and Multiple Myeloma Microarray Gene Expression Data 

    Liu, Qingzhong; Sung, Andrew H.; Chen, Zhongxue; Huang, Xudong; Deng, Youpin; Liu, Jianzhong (PLoS ONE, 2009-12-11)
    Microarray data has a high dimension of variables but available datasets usually have only a small number of samples, thereby making the study of such datasets interesting and challenging. In the task of analyzing microarray ...

  • A gene selection method for GeneChip array data with small sample sizes 

    Chen, Zhongxue; Liu, Qingzhong; McGee, Monnie; Kong, Megan; Huang, Xudong; Deng, Youpin; Scheuermann, Richard H. (2010-07)
    In microarray experiments with small sample sizes, it is a challenge to estimate p-values accurately and decide cutoff p-values for gene selection appropriately. Although permutation-based methods have proved to have ...

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