GRIFFIN: a system for predicting GPCR-G-protein coupling selectivity using a support vector machine and a hidden Markov model.

GRIFFIN: a system for predicting GPCR-G-protein coupling selectivity using a support vector machine and a hidden Markov model.
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Griffin:使用支持向量机和隐藏的Markov模型预测GPCR-G蛋白耦合选择性的系统。

DOI:
10.1093/nar/gki495
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发表时间:
2005-07-01
影响因子:
14.9
通讯作者:
Suwa, M
Suwa, M
中科院分区:
生物学2区
文献类型:
--
作者:
Yabuki, Y;Muramatsu, T;Hirokawa, T;Mukai, H;Suwa, M

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我们描述了一种新的系统,GRIFFIN(G蛋白和受体相互作用特征发现INCIDOR),预测G蛋白偶联受体(GPCR)和G蛋白偶联选择性的支持向量机(SVM)和隐马尔可夫模型(HMM)的基础上,具有高灵敏度和特异性。基于配体、GPCR和G蛋白的整个结构片段是确定GPCR和G蛋白偶联所必需的假设,为配体、GPCR和G蛋白复合物结构选择各种定量特征,并将那些在选择G蛋白类型中最有效的参数用作SVM中的特征向量。GRIFFIN的主要部分包括一个使用特征向量的分层SVM分类器,这对A类GPCR(主要家族)很有用。对于A类和其他小家族(B类、C类、卷曲的和平滑的)的视蛋白和嗅觉亚家族,使用HMM以高精度预测结合G蛋白。将该系统应用于已知的GPCR序列,以高灵敏度和特异性(平均>85%)预测每个结合G蛋白。GRIFFIN()是免费提供的,允许用户轻松执行G蛋白的可靠预测。
We describe a novel system, GRIFFIN (G-protein and Receptor Interaction Feature Finding INstrument), that predicts G-protein coupled receptor (GPCR) and G-protein coupling selectivity based on a support vector machine (SVM) and a hidden Markov model (HMM) with high sensitivity and specificity. Based on our assumption that whole structural segments of ligands, GPCRs and G-proteins are essential to determine GPCR and G-protein coupling, various quantitative features were selected for ligands, GPCRs and G-protein complex structures, and those parameters that are the most effective in selecting G-protein type were used as feature vectors in the SVM. The main part of GRIFFIN includes a hierarchical SVM classifier using the feature vectors, which is useful for Class A GPCRs, the major family. For the opsins and olfactory subfamilies of Class A and other minor families (Classes B, C, frizzled and smoothened), the binding G-protein is predicted with high accuracy using the HMM. Applying this system to known GPCR sequences, each binding G-protein is predicted with high sensitivity and specificity (>85% on average). GRIFFIN () is freely available and allows users to easily execute this reliable prediction of G-proteins.
DOI: 10.1093/bioinformatics/17.7.646
发表时间: 2001-07-01
期刊: BIOINFORMATICS
影响因子: 5.8
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Möller, S;Croning, MDR;Apweiler, R
通讯作者: Apweiler, R
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发表时间: 2003-01-01
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发表时间: 2004-12-12
期刊: BIOINFORMATICS
影响因子: 5.8
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通讯作者: Gulukota, K
DOI: 10.1073/pnas.85.8.2444
发表时间: 1988-04-01
影响因子: 11.1
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通讯作者: LIPMAN, DJ