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A new approach for gene prediction using comparative sequence analysis

机译:使用比较序列分析进行基因预测的新方法

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The availability of large fragments of genomic DNA makes it possible to apply comparative genomics for identification of protein-coding regions. In this work, a comparative analysis is conducted on homologous genomic sequences of organisms with different evolutionary distances and the conservation of the non-coding regions between closely related organisms is found. In contrast, more distance shows much less intron similarity but less conservation on the exon structures. This study sought to illuminate the impact of evolutionary distances on the performance of the proposed gene-finding program based on the cross-species sequence comparison. Base on the finding from comparative study and training of data sets, we proposed a model by which coding sequence could be identified by comparing sequences of multiple species, both close and approximately distant. The reliability of the proposed method is evaluated in terms of sensitivity and specificity, and results are compared to those obtained by other popular gene prediction programs. Provided sequences can be found from other species at appropriate evolutionary distances, this approach could be applied in newly sequenced organisms where no species-dependent statistical models are available.
机译:基因组DNA的大片段的可用性使得可以应用比较基因组学用于鉴定蛋白质编码区。在这项工作中,对具有不同进化距离的生物的同源基因组序列进行比较分析,发现密切相关的生物之间的非编码区的保护。相比之下,更多距离显示出的内含子相似度较少,但在外显子结构上的保守较少。本研究寻求利用进化距离基于跨物种序列比较来照亮进化距离对所提出的基因查找计划的性能的影响。基于数据集的比较研究和培训的发现,我们提出了一种模型,可以通过比较多种物种的序列来识别编码序列,既近似和近似遥远。在敏感性和特异性方面评估所提出的方法的可靠性,并将结果与​​其他受欢迎的基因预测计划获得的结果进行比较。提供的序列可以在适当的进化距离下从其他物种中发现,这种方法可以应用于新序列的生物,其中没有可依赖于依赖性统计模型。

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