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A Comparative Study of Content Statistics of Coding Regions in an Evolutionary Computation Framework for Gene Prediction

机译:基因预测进化计算框架中编码区内容统计的比较研究

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The determination of which parts of a DNA sequence are coding is an unsolved and relevant problem in the field of bioinformatics. This problem is called gene prediction or gene finding, and it consists of locating the most likely gene structure in a genomic sequence. Taking into account some restrictions, gene structure prediction may be considered as a search problem. To address the problem, evolutionary computation approaches can be used, although their performance will depend on the discriminative power of the statistical measures employed to extract useful features from the sequence. In this study, we test six different content statistics to determine which of them have higher relevance in an evolutionary search for coding and non-coding regions of human DNA. We conduct this comparative study on the human chromosomes 3, 19 and 21.
机译:测定DNA序列的哪些部分是编码的是生物信息学领域的未解决和相关问题。该问题称为基因预测或基因发现,并且它包括以基因组序列定位最可能的基因结构。考虑到一些限制,基因结构预测可以被认为是搜索问题。为了解决问题,可以使用进化计算方法,尽管它们的性能取决于所用序列中提取有用特征的统计措施的辨别力。在这项研究中,我们测试六种不同的内容统计,以确定其中哪一个在进化中搜索人类DNA的编码和非编码区域中的相关性更高。我们对人染色体3,19和21进行该比较研究。

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