Hidden Markov models
Hidden Markov models
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DOI：
10.1016/s0959-440x(96)80056-x
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发表时间：
1996-06-01
影响因子：
6.8
通讯作者：
Eddy, SR
中科院分区：
文献类型：
--
作者：
Eddy, SR
蛋白质结构和序列比对的“图谱”可以检测出细微的同源性。通过引入隐马尔可夫模型（HMM）方法，轮廓分析已经建立在更坚实的数学基础上。在过去的一年中，这些强大的新的基于HMM的配置文件的应用已经开始出现在蛋白质结构预测和大规模基因组序列分析领域。
'Profiles' of protein structures and sequence alignments can detect subtle homologies. Profile analysis has been put on firmer mathematical ground by the introduction of hidden Markov model (HMM) methods. During the past year, applications of these powerful new HMM-based profiles have begun to appear in the fields of protein-structure prediction and large-scale genome-sequence analysis.