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COMBINING N-GRAMS AND ALIGNMENT IN G-PROTEIN COUPLING SPECIFICITY PREDICTION

机译:结合N-克和对准在G蛋白偶联特异性预测中

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G-protein coupled receptors (GPCR) interact with G-proteins to regulate much of the cell's response to external stimuli; abnormalities in which cause numerous diseases. We developed a new method to predict the families of G-proteins with which it interacts, given its residue sequence. We combine both alignment and n-gram features. The former captures long-range interactions but assumes the linear ordering of conserved segments is preserved. The latter makes no such assumption but cannot capture long-range interactions. By combining alignment and n-gram features, and using the entire GPCR sequence (instead of intracellular regions alone, as was done by others), our method outperformed the current state-of-the-art in precision, recall and Fl, attaining 0.753 in Fl and 0.796 in accuracy on the PTbase 2004 dataset. Moreover, analysis of our results shows that the majority of coupling specificity information lies in the beginning of the 2nd intracellular loop and over the length of the 3rd.
机译:G-蛋白偶联受体(GPCR)与G-蛋白相互作用以调节大部分细胞对外部刺激的反应;异常引起众多疾病。我们开发了一种预测其残留序列的G-蛋白的家族的一种新方法。我们结合了对齐和N-GRAM功能。前者捕获远程相互作用,但假设保存段的线性排序被保留。后者没有这样的假设,但不能捕获远程相互作用。通过组合对准和N-GRAM特征,并使用整个GPCR序列(而不是由其他人单独使用的细胞内区域),我们的方法在精确度,召回和FL中表现出目前的最先进,达到0.753在PTBase 2004数据集中的精度为FL和0.796。此外,我们的结果分析表明,大多数偶联特异性信息在于第二内环的开始和3RD的长度。

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