隐马尔可夫模型预测信号肽和信号锚点。

H Nielsen, A Krogh
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引用次数: 0

摘要

建立了信号肽的隐马尔可夫模型。它包含n端部分、疏水区域和解理位点周围区域的子模型。对于已知的信号肽,该模型可用于在这三个区域之间分配客观边界。应用于我们的数据,三个地区的长度分布与预期显著不同。例如,在几乎所有真核生物的信号肽中,指定的疏水区域长度在8到12个残基之间。这一分析也表明真核生物、革兰氏阳性菌和革兰氏阴性菌之间存在明显的差异。该模型可用于预测切割位点的位置,在交叉验证测试中,它在近70%的信号肽中找到了正确的位置-几乎与之前最好的方法相同的准确性。现有预测方法的问题之一是信号肽和未裂解信号锚点之间的区别较差,但当将隐马尔可夫模型扩展到一个非常简单的信号锚点模型时,这一问题得到了极大的改善。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction of signal peptides and signal anchors by a hidden Markov model.

A hidden Markov model of signal peptides has been developed. It contains submodels for the N-terminal part, the hydrophobic region, and the region around the cleavage site. For known signal peptides, the model can be used to assign objective boundaries between these three regions. Applied to our data, the length distributions for the three regions are significantly different from expectations. For instance, the assigned hydrophobic region is between 8 and 12 residues long in almost all eukaryotic signal peptides. This analysis also makes obvious the difference between eukaryotes, Gram-positive bacteria, and Gram-negative bacteria. The model can be used to predict the location of the cleavage site, which it finds correctly in nearly 70% of signal peptides in a cross-validated test--almost the same accuracy as the best previous method. One of the problems for existing prediction methods is the poor discrimination between signal peptides and uncleaved signal anchors, but this is substantially improved by the hidden Markov model when expanding it with a very simple signal anchor model.

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