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PredCRP: predicting and analysing the regulatory roles of CRP from its binding sites in Escherichia coli.
Scientific Reports ( IF 3.8 ) Pub Date : 2018-01-17 , DOI: 10.1038/s41598-017-18648-5
Ming-Ju Tsai , Jyun-Rong Wang , Chi-Dung Yang , Kuo-Ching Kao , Wen-Lin Huang , Hsi-Yuan Huang , Ching-Ping Tseng , Hsien-Da Huang , Shinn-Ying Ho

Cyclic AMP receptor protein (CRP), a global regulator in Escherichia coli, regulates more than 180 genes via two roles: activation and repression. Few methods are available for predicting the regulatory roles from the binding sites of transcription factors. This work proposes an accurate method PredCRP to derive an optimised model (named PredCRP-model) and a set of four interpretable rules (named PredCRP-ruleset) for predicting and analysing the regulatory roles of CRP from sequences of CRP-binding sites. A dataset consisting of 169 CRP-binding sites with regulatory roles strongly supported by evidence was compiled. The PredCRP-model, using 12 informative features of CRP-binding sites, and cooperating with a support vector machine achieved a training and test accuracy of 0.98 and 0.93, respectively. PredCRP-ruleset has two activation rules and two repression rules derived using the 12 features and the decision tree method C4.5. This work further screened and identified 23 previously unobserved regulatory interactions in Escherichia coli. Using quantitative PCR for validation, PredCRP-model and PredCRP-ruleset achieved a test accuracy of 0.96 (=22/23) and 0.91 (=21/23), respectively. The proposed method is suitable for designing predictors for regulatory roles of all global regulators in Escherichia coli. PredCRP can be accessed at https://github.com/NctuICLab/PredCRP .

中文翻译:

PredCRP:从其在大肠杆菌中的结合位点预测和分析CRP的调控作用。

环状AMP受体蛋白(CRP)是大肠杆菌中的一种全球调节物,它通过两个作用来调节180多个基因:激活和抑制。很少有方法可以从转录因子的结合位点预测调节作用。这项工作提出了一种精确的方法PredCRP来推导优化模型(称为PredCRP-模型)和一组四个可解释的规则(称为PredCRP-规则集),用于预测和分析CRP结合位点序列对CRP的调控作用。汇编了由169个CRP结合位点组成的数据集,这些位点在证据的强烈支持下具有监管作用。PredCRP模型利用CRP结合位点的12种信息特征,并与支持向量机配合使用,分别获得了0.98和0.93的训练和测试精度。PredCRP规则集具有两个激活规则和两个抑制规则,这些规则是使用12个功能和决策树方法C4.5派生的。这项工作进一步筛选和鉴定了23种以前在大肠杆菌中未观察到的调节相互作用。使用定量PCR进行验证,PredCRP模型和PredCRP规则集分别达到0.96(= 22/23)和0.91(= 21/23)的测试准确度。所提出的方法适合于设计用于大肠杆菌中所有全球调节剂的调节作用的预测因子。可以从https://github.com/NctuICLab/PredCRP访问PredCRP。PredCRP模型和PredCRP规则集分别达到0.96(= 22/23)和0.91(= 21/23)的测试精度。所提出的方法适合于设计用于大肠杆菌中所有全球调节剂的调节作用的预测因子。可以从https://github.com/NctuICLab/PredCRP访问PredCRP。PredCRP模型和PredCRP规则集分别达到0.96(= 22/23)和0.91(= 21/23)的测试精度。所提出的方法适合于设计用于大肠杆菌中所有全球调节剂的调节作用的预测因子。可以从https://github.com/NctuICLab/PredCRP访问PredCRP。
更新日期:2018-01-17
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