SBP-SITA: A sequence-based prediction tool for S-itaconation
SBP-SITA: A sequence-based prediction tool for S-itaconation
Abstract As a recently-reported post-translational modification, S-itaconation plays an important role in inflammation suppression. In order to understand its regulatory mechanism in many life activities, the essential step is the recognition of S-itaconation. However, it is difficult to identify S-itaconation in the proteome for the high cost, which limits further investigation. In this study, we constructed an ensemble algorithm based on Soft Voting Classifier. The area under the ROC curve (AUC) value 0.73 for ensemble model. Accordingly, we constructed the on-line prediction tool dubbed SBP-SITA for easily identifying Cystine sites. SBP-SITA is available at http://www.bioinfogo.org/sbp-sita.
Zhang Laizhi、Wang Xuanwen、Meng Yanzheng、Chen Yu、Li Lei、Wang Ziyu、Zhang Lin
School of Basic Medicine, Qingdao UniversityCollege of Computer Science and technology, Qingdao UniversitySchool of Basic Medicine, Qingdao UniversityCollege of Computer Science and technology, Qingdao UniversitySchool of Basic Medicine, Qingdao UniversitySchool of Basic Medicine, Qingdao UniversityCollege of Computer Science and technology, Qingdao University
生物化学分子生物学生物科学研究方法、生物科学研究技术
machine learning1post-translational modification2itaconation3cysteine4prediction5
Zhang Laizhi,Wang Xuanwen,Meng Yanzheng,Chen Yu,Li Lei,Wang Ziyu,Zhang Lin.SBP-SITA: A sequence-based prediction tool for S-itaconation[EB/OL].(2025-03-28)[2025-04-30].https://www.biorxiv.org/content/10.1101/2021.12.13.472522.点此复制
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