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Predicting secretory protein signal sequence cleavage sites by fusing the marks of global alignments

机译:通过融合整体比对标记来预测分泌蛋白信号序列的切割位点

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摘要

A newly synthesized secretory protein in cells bears a special sequence, called signal peptide or sequence, which plays the role of "address tag" in guiding the protein to wherever it is needed. Such a unique function of signal sequences has stimulated novel strategies for drug design or reprogramming cells for gene therapy. To realize these new ideas and plans, however, it is important to develop an automated method for fast and accurately identifying the signal sequences or their cleavage sites. In this paper, a new method is developed for predicting the signal sequence of a query secretory protein by fusing the results from a series of global alignments through a voting system. The very high success rates thus obtained suggest that the novel approach is very promising, and that the new method may become a useful vehicle in identifying signal sequence, or at least serve as a complementary tool to the existing algorithms of this field.
机译:细胞中新合成的分泌蛋白具有特殊的序列,称为信号肽或序列,在将蛋白引导至所需位置时起“地址标签”的作用。信号序列的这种独特功能刺激了药物设计或细胞重编程以进行基因治疗的新策略。然而,为了实现这些新的想法和计划,重要的是开发一种自动方法来快速准确地识别信号序列或其切割位点。在本文中,开发了一种新方法,该方法可通过表决系统融合一系列全局比对的结果来预测查询分泌蛋白的信号序列。因此获得的非常高的成功率表明,该新方法非常有前途,并且该新方法可能成为识别信号序列的有用工具,或者至少充当该领域现有算法的补充工具。

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