Differentially expressed gene

A new method for estimating the number of non-differentially expressed genes

J. Wu, Liu, C. Y., Chen, W. T., Ma, W. Y., Ding, Y., Wu, J., Liu, C. Y., Chen, W. T., Ma, W. Y., Ding, Y., Wu, J., Liu, C. Y., Chen, W. T., Ma, W. Y., and Ding, Y., “A new method for estimating the number of non-differentially expressed genes”, vol. 15, p. -, 2016.

Control of the false discovery rate is a statistical method that is widely used when identifying differentially expressed genes in high-throughput sequencing assays. It is often calculated using an adaptive linear step-up procedure in which the number of non-differentially expressed genes should be estimated accurately. In this paper, we discuss the estimation of this parameter and point out defects in the original estimation method. We also propose a new estimation method and provide the error estimation.

An expression profiling analysis of hybrid millet and its parents at grain filling stage

Z. H. Liu, Zhang, H. M., Li, G. L., Zhang, Y. M., Li, H. C., and Guo, X. L., “An expression profiling analysis of hybrid millet and its parents at grain filling stage”, vol. 14, pp. 7821-7832, 2015.

Heterosis has been widely used in crop breeding and production. However, a shortage of genes known to function in heterosis significantly limits our understanding of the molecular basis underlying heterosis. Here, we report 740 differentially expressed genes (DEGs) in the leaves of the hybrid millet Zhang No.5 and its parents at the grain filling stage determined using Solexa Illumina digital gene expression. Of the 740 DEGs, 546 were from the hybrid and its parents and most were up-regulated in the hybrid.

Integrated microRNA-mRNA analysis of pancreatic ductal adenocarcinoma

P. F. Liu, Jiang, W. H., Han, Y. T., He, L. F., Zhang, H. L., and Ren, H., “Integrated microRNA-mRNA analysis of pancreatic ductal adenocarcinoma”, vol. 14, pp. 10288-10297, 2015.

The main aim of this study was to explore the underlying molecular mechanisms and potential target molecules of pancreatic adenocarcinoma. The miRNA (GSE32678) and mRNA (GSE32676) expression profiles of patients with pancreatic ductal adenocarcinoma and healthy controls were downloaded from the Gene Expression Omnibus database. Differentially expressed miRNA and differentially expressed genes were identified by analyzing the microarray algorithm after data preprocessing. Functional analysis was conducted by the Database for Annotation, Visualization and Integrated Analysis.

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