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• W2996238637 endingPage "75" @default.
• W2996238637 startingPage "75" @default.
• W2996238637 abstract "Understanding of quorum-sensing peptides (QSPs) in their functional mechanism plays an essential role in finding new opportunities to combat bacterial infections by designing drugs. With the avalanche of the newly available peptide sequences in the post-genomic age, it is highly desirable to develop a computational model for efficient, rapid and high-throughput QSP identification purely based on the peptide sequence information alone. Although, few methods have been developed for predicting QSPs, their prediction accuracy and interpretability still requires further improvements. Thus, in this work, we proposed an accurate sequence-based predictor (called iQSP) and a set of interpretable rules (called IR-QSP) for predicting and analyzing QSPs. In iQSP, we utilized a powerful support vector machine (SVM) cooperating with 18 informative features from physicochemical properties (PCPs). Rigorous independent validation test showed that iQSP achieved maximum accuracy and MCC of 93.00% and 0.86, respectively. Furthermore, a set of interpretable rules IR-QSP was extracted by using random forest model and the 18 informative PCPs. Finally, for the convenience of experimental scientists, the iQSP web server was established and made freely available online. It is anticipated that iQSP will become a useful tool or at least as a complementary existing method for predicting and analyzing QSPs." @default.
• W2996238637 created "2019-12-26" @default.
• W2996238637 creator A5004093986 @default.
• W2996238637 creator A5037914988 @default.
• W2996238637 creator A5043577834 @default.
• W2996238637 creator A5069155677 @default.
• W2996238637 creator A5084444175 @default.
• W2996238637 date "2019-12-20" @default.
• W2996238637 modified "2023-10-12" @default.
• W2996238637 title "iQSP: A Sequence-Based Tool for the Prediction and Analysis of Quorum Sensing Peptides Using Informative Physicochemical Properties" @default.
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