HybridSucc: A Hybrid-learning Architecture for General and Species-specific Succinylation Site Prediction.

HybridSucc: A Hybrid-learning Architecture for General and Species-specific Succinylation Site Prediction.
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HybridSucc:用于一般和物种特异性琥珀酰化位点预测的混合学习架构

DOI:
10.1016/j.gpb.2019.11.010
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发表时间:
2020-04
期刊:
Genomics, proteomics & bioinformatics
影响因子:
--
通讯作者:
Xue Y
Xue Y
中科院分区:
其他
文献类型:
--
作者:
Ning W;Xu H;Jiang P;Cheng H;Deng W;Guo Y;Xue Y

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赖氨酸琥珀酰化(Ksucc)是一种重要的蛋白质酰化修饰,参与多种生物学过程,并参与人类肿瘤的发生。在这里,我们收集了来自13个物种的26,243个非冗余已知Ksucc站点作为基准数据集,结合了10种信息特征,并通过将深度学习和传统机器学习算法集成到一个框架中来实现混合学习架构。我们构建了一个名为HybridSucc的新工具,该工具分别实现了Ksucc位点的一般和人类特异性预测的曲线下面积(AUC)值为0.885和0.952。相比之下,HybridSucc的准确率比其他现有工具高17.84%-50.62%。使用HybridSucc,我们进行了蛋白质组范围的预测,并优先考虑了370种癌症突变,这些突变改变了218种重要蛋白质的Ksucc状态,包括PKM 2,SHMT 2和IDH 2。我们不仅开发了一个高调的工具来预测Ksucc网站,但也产生了有用的候选人进一步的实验考虑。HybridSucc的在线服务可以在http://hybridsucc.biocuckoo.org/上免费访问。
As an important protein acylation modification, lysine succinylation (Ksucc) is involved in diverse biological processes, and participates in human tumorigenesis. Here, we collected 26,243 non-redundant known Ksucc sites from 13 species as the benchmark data set, combined 10 types of informative features, and implemented a hybrid-learning architecture by integrating deep-learning and conventional machine-learning algorithms into a single framework. We constructed a new tool named HybridSucc, which achieved area under curve (AUC) values of 0.885 and 0.952 for general and human-specific prediction of Ksucc sites, respectively. In comparison, the accuracy of HybridSucc was 17.84%–50.62% better than that of other existing tools. Using HybridSucc, we conducted a proteome-wide prediction and prioritized 370 cancer mutations that change Ksucc states of 218 important proteins, including PKM2, SHMT2, and IDH2. We not only developed a high-profile tool for predicting Ksucc sites, but also generated useful candidates for further experimental consideration. The online service of HybridSucc can be freely accessed for academic research at http://hybridsucc.biocuckoo.org/.
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