| HMM用于G蛋白偶联受体超家族的识别 |
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| 引用本文： | 侯永丰,李通化.HMM用于G蛋白偶联受体超家族的识别[J].同济大学学报(自然科学版),2004,32(12):1696-1700. |
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| 作者姓名： | 侯永丰 李通化 |
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| 作者单位： | 同济大学,化学系,上海,200092 |
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| 基金项目： | 国家自然科学基金资助项目 (2 0 2 75 0 2 6) |
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| 摘 要： | 采用了一种HMM(隐马尔可夫模型 )的方法用于G蛋白偶联受体超家族层次各类别之间进行识别 ,具体考虑了ACDE与B类超家族 ,以及BCDE与A类超家族的分辨 ,取得了不错的效果 ,类之间的识别准确率可以达到10 0 % .研究过程中 ,考虑了G蛋白偶联受体一级结构信息和数据自身特性 ,合理地利用了G蛋白偶联受体一级结构序列的不等长特性 ,同时在模型的预测方面采用了双模型的预测机制 .
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| 关 键 词： | G蛋白偶联受体 隐马尔可夫模型 分类 信息系统 |
| 文章编号： | 0253-374X(2004)12-1696-05 |
Classifying G-protein Coupled Receptors with Hidden Markov Models |
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| HOU Yong-feng,LI Tong-hua.Classifying G-protein Coupled Receptors with Hidden Markov Models[J].Journal of Tongji University(Natural Science),2004,32(12):1696-1700. |
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| Authors: | HOU Yong-feng LI Tong-hua |
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| Abstract: | G protein coupled receptors are the most numerous types of cell proteins in the body and are the target agents for approximately 50 percent of the drugs on the market today. We applied hidden Markov model in classifying G protein coupled receptors, tested the discrimination of ACDE and B superfamily , together with BCDE and A superfamily concretely, and a good result was achieved.Hidden Markov models can integrate G protein coupled receptors data features into a model.Experiment results suggest hidden Markov models is well fit to classifying G protein coupled receptors with length-variable primary sequences. |
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| Keywords: | G protein coupled receptors hidden Markov models classification information system |
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