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首页> 外文会议>International symposium on bioinformatics research and applications >DNA AS X: An Information-Coding-Based Model to Improve the Sensitivity in Comparative Gene Analysis
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DNA AS X: An Information-Coding-Based Model to Improve the Sensitivity in Comparative Gene Analysis

机译：DNA AS X：一种基于信息编码的模型，可提高比较基因分析的敏感性

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摘要

In recent studies, lots of hidden homology in DNA genome are not found by current comparative tools despite decades of research. Many scholars modeled the genome as a monotonous string, which limits and probably obstructs the discovery of some significant patterns. We propose an information-coding-based model called DNA As X (DAX) to improve the sensitivity in comparative genomic studies by integrating the principles and concepts of other disciplines including information coding theory and signal processing into genome analysis. The proposed DNA As X model uses character-analysis-free (CAF) techniques, where X is the intermediate for analysis that can be digit, code, signal, vector, tree, graph network and so on. It provides novel and comprehensive perspectives to further analyze and recognize the critical patterns hidden in DNA genomes. Comparing with traditional character-analysis-based (CAB) methods, DAX not only enriches the tools and the knowledge library of computational biology but also extends the domain from 1-D character string analysis to 2-D spatial/temporal domain. Furthermore, by applying the DAX model to the issue of exon prediction as an evaluation, we illustrate the insights behind this model. The experimental results show that the DAX methodology can improve the sensitivity in genome analysis by using the novel information-coding techniques.
机译：在最近的研究中，尽管进行了数十年的研究，但当前的比较工具并未发现DNA基因组中许多隐藏的同源性。许多学者将基因组建模为单调的字符串，这限制了并可能阻碍了一些重要模式的发现。我们提出了一个基于信息编码的模型，称为DNA As X（DAX），通过将包括信息编码理论和信号处理在内的其他学科的原理和概念整合到基因组分析中，从而提高了比较基因组研究的敏感性。提出的DNA As X模型使用无字符分析（CAF）技术，其中X是分析的中间物，可以是数字，代码，信号，矢量，树，图形网络等。它提供了新颖而全面的观点，可以进一步分析和识别隐藏在DNA基因组中的关键模式。与传统的基于字符分析的（CAB）方法相比，DAX不仅丰富了计算生物学的工具和知识库，而且将范围从一维字符串分析扩展到了二维空间/时间域。此外，通过将DAX模型应用于外显子预测问题作为评估，我们说明了该模型背后的见解。实验结果表明，DAX方法可以通过使用新型信息编码技术提高基因组分析的灵敏度。

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