Detecting Subtle Sequence Signals: A Gibbs Sampling Strategy for Multiple Alignment |
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| 文献名称 | Detecting Subtle Sequence Signals: A Gibbs Sampling Strategy for Multiple Alignment | ||||||
| 文献作者 | Charles E. Lawrence; Stephen F. Altschul; Mark S. Boguski; Jun S. Liu; Andrew F. Neuwald;John C. Wootton | ||||||
| 作者所在单位 | C. E. Lawrence, S. F. Altschul, M. S. Boguski, A. F.Neuwald, and J. C. Wootton are with the National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda MD 20894. J. S. Liu is with the Statistics Dep | ||||||
| 文献分类 | 已发表文献 | ||||||
| 学科一级分类 | 统计 | ||||||
| 学科二级分类 | 统计学 | ||||||
| 文献摘要 |
A wealth of protein and DNA sequence data is being generated by genome projects and other sequencing efforts. A crucial barrier to deciphering these sequences and understanding the relationsamongthem isthe difficulty of detectingsubtle local residue patterns common to multiple sequences. Such patterns frequently reflect similar molecular structures and biologicalproperties.A mathematical definition of this "local multiple alignment" problem suitable for full computer automation has been used to develop a new and sensitive algorithm, based on the statistical method of iterative sampling. This algorithm finds an optimized local alignment model for Nsequences in Nlinear time, requiring only seconds on current workstations, and allows the simultaneous detection and optimization of multiple patterns and pattern repeats. The method is illustrated as applied to helixturn- helix proteins, lipocalins, and prenyltransferases. |
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| 参考文献 |
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| 关键字 | Subtle Sequence Signals ;A Gibbs Sampling Strategy ; Multiple Alignment | ||||||
| 发表所在刊物（或来源） | Science, New Series, Vol. 262, No. 5131. (Oct. 8, 1993), pp. 208-214 | ||||||
| 发表时间 | Oct. 8, 1993 | ||||||
| 适用研究领域 | 统计学 | ||||||
| 评论 | |||||||
| 上传时间 | 2011-1-19 18:09 | ||||||
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