Chun-Fa Tong

Nanjing Forestry University, Nan-ching, Jiangsu Sheng, China

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Publications (3)0 Total impact

  • Wen-Juan Shan · Chun-Fa Tong · Ji-Sen Shi
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    ABSTRACT: DNA microarray is a new tool in biotechnology, which allows simultaneously monitoring thousands of gene expression in cells. The goal of differential gene expression analysis is to detect genes with significant change of gene expression levels arising from experimental conditions. Although various statistical methods have been suggested to confirm differential gene expression, only a few studies compared performance of the statistical methods. This paper presented comparison of statistical methods for finding differentially expressed genes (DEGs) from the microarray data. Using simulated and real datasets (Populus cDNA microarray data), we compared eight methods of identifying differential gene expression. The simulated datasets included four differential distributions (normal distribution, uniform distribution, c2 distribution, and exponential distribution). The results of simulated datasets analysis showed that the eight methods were more preferable with the microarray data of uniform distribution than normal distribution. They were not preferable with the c2 distribution and exponential distribution. Of these eight methods, SAM (Significance Analysis of Microarrays) and Wilcoxon rank sum test performed well in most cases. The results of real cDNA microarray data of Populus showed that there was much similarity of SAM, Samroc, and regression modeling approach. Wilcoxon rank sum test was different from them. Samroc and regression modeling approach were similar in the eight methods. For both simulated and real datasets, SAM, Samroc, and regression modeling approach performed better than other methods.
    No preview · Article · Jan 2009 · Hereditas (Beijing)
  • Meng Zhou · Chun-Fa Tong · Ji-Sen Shi
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    ABSTRACT: Poplar is among the most important deciduous tree species in plantations over the world and has been used as an important model system for molecular genetics of trees. The analysis of codon usage may improve the understanding of the mechanism of codon distribution and variation in poplar and the understanding of factors shaping the codon usage patterns. Here, an EN(c) (effective number of codons)-plot method and multivariate statistical method called correspondence analysis (COA) were used to examine the codon usage of 314 genes of poplar. The results show that the main trend was highly negative correlated with the gene expression level assessed by the ''Codon Adaptation Index'' value. Moreover, there were two significant correlations between axis 1 coordinates and GC3(s) content and gene length, we infer that gene nucleotide composition and gene length also play an important role in shaping the codon usage bias in poplar. The result of relative synonymous codon usage (RSCU) analysis shows a high bias of codon usage toward the codon with A or T ending. In addition, we compared the codon preferences among poplar, Arabidopsis thaliana, Oryza sative, Homo sapiens and Escherichia coli, and poplar was found to be most similar to A.thaliana and least similar to E.coli. In this paper, 10 codons defined firstly as optimal codons through an analysis of the high-expression codon in poplar may provide some useful information for genetic engineering of poplar.
    No preview · Article · Sep 2007 · Zhi wu sheng li yu fen zi sheng wu xue xue bao = Journal of plant physiology and molecular biology
  • Chun-fa Tong · Ji-sen Shi

    No preview · Article · Jan 2005