Identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites
Identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites
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DOI：
10.1093/protein/10.1.1
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发表时间：
1997-01-01
期刊：
影响因子：
--
通讯作者：
vonHeijne, G
中科院分区：
文献类型：
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作者：
Nielsen, H;Engelbrecht, J;vonHeijne, G
我们开发了一种基于在不同的原核和真核序列组上训练的神经网络来识别信号肽及其切割位点的新方法。该方法的性能明显优于以前的预测方案，并且可以轻松应用于全基因组数据集。切割的信号肽和未切割的 N 端信号锚序列之间的区分也是可能的，但精度较低。可以在公共可用的 WWW 服务器上进行预测。
We have developed a new method for the identification of signal peptides and their cleavage sites based on neural networks trained on separate sets of prokaryotic and eukaryotic sequence. The method performs significantly better than previous prediction schemes and can easily be applied on genome-wide data sets. Discrimination between cleaved signal peptides and uncleaved N-terminal signal-anchor sequences is also possible, though with lower precision. Predictions can be made on a publicly available WWW server.