SignalP 6.0 使用蛋白质语言模型预测所有五种类型的信号肽。
SignalP 6.0 predicts all five types of signal peptides using protein language models.
机构信息
Section for Bioinformatics, Department of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark.
Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
出版信息
Nat Biotechnol. 2022 Jul;40(7):1023-1025. doi: 10.1038/s41587-021-01156-3. Epub 2022 Jan 3.
Signal peptides (SPs) are short amino acid sequences that control protein secretion and translocation in all living organisms. SPs can be predicted from sequence data, but existing algorithms are unable to detect all known types of SPs. We introduce SignalP 6.0, a machine learning model that detects all five SP types and is applicable to metagenomic data.
信号肽（SPs）是控制所有生物体内蛋白质分泌和转运的短氨基酸序列。SP 可以从序列数据中预测，但现有的算法无法检测到所有已知类型的 SPs。我们引入了 SignalP 6.0，这是一种机器学习模型，可检测所有五种 SP 类型，并且适用于宏基因组数据。
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