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Differential expression analysis based on “next-generation” sequencing technologies is a fundamental means of studying RNA expression. We recently developed a multi-step normalization method (called TbT) for two-group RNA-seq data with replicates and demonstrated that the statistical methods available in four R packages (edgeR, DESeq, baySeq, and NBPSeq)(More)
Nowadays, people usually depend on augmented reality (AR) systems to obtain an augmented view in a real-world environment. With the help of advanced AR technology (e.g. object recognition), users can effectively distinguish multiple objects of different types. However, these techniques can only offer limited degrees of distinctions among different objects(More)
The core circadian oscillator of cyanobacteria consists of three proteins, KaiA, KaiB, and KaiC. This circadian oscillator could be functionally reconstituted in vitro with these three proteins, and therefore has been a very important model in circadian rhythm research. KaiA can bind to KaiC and then stimulate its phosphorylation, but their interaction(More)
The processive phosphorylation mechanism becomes important when there is macromolecular crowding in the cytoplasm. Integrating the processive phosphorylation mechanism with the traditional distributive one, we propose a mixed dual-site phosphorylation (MDP) mechanism in a single-layer phosphorylation cycle. Further, we build a degree model by applying the(More)
RNA-seq is a powerful tool for measuring transcriptomes, especially for identifying differentially expressed genes or transcripts (DEGs) between sample groups. A number of methods have been developed for this task, and several evaluation studies have also been reported. However, those evaluations so far have been restricted to two-group comparisons.(More)
We use methods of random matrix theory (RMT) to investigate the information content of the cross correlation matrix C of Shanghai stock exchange (SSE) for the period Jan 2, 2001 to May 30, 2008. We find that, the statistics of most of the eigenvalues in the spectrum of C agree with the predictions of random matrix theory, 92.6% of the eigenvalues fall(More)
  • Jianqiang Sun
  • 2008
We apply the random-matrix approach to undress the noise of the cross correlation matrix constructed from Shanghai Stock Exchange (SSE) for the period 2001-2008. The empirical evidence shows that, about 7.4% of the eigenvalues fall out the RMT bounds, and the eigenvalues within the bounds agree with the universal properties of random matrix, implying a(More)
A quasi-analytical pricing method for arithmetic Asian option is presented based on an approximate relation between the geometric and arithmetic average of the log-normal random variables. With a generalized mean function, we use a Taylor expansion in terms of the geometric average value of the underlying assets to approximate the arithmetic average value.(More)