HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment
HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment
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DOI：
10.1038/nmeth.1818
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发表时间：
2012-02-01
期刊：
影响因子：
48
通讯作者：
Soeding, Johannes
中科院分区：
文献类型：
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作者：
Remmert, Michael;Biegert, Andreas;Soeding, Johannes
基于序列的蛋白质功能和结构预测在很大程度上取决于序列搜索灵敏度和所得序列比对的准确性。我们提出了一个开源的，通用的工具，表示查询和数据库序列的轮廓隐马尔可夫模型（HMM）：“基于HMM-HMM闪电般快速迭代序列搜索”（HHblits; http：//toolkit.genzentrum.lmu.de/hhblits/）。与序列搜索工具PSI-BLAST相比，HHblits由于其离散化配置文件预过滤器而更快，灵敏度高50-100%，并且生成更准确的比对。
Sequence-based protein function and structure prediction depends crucially on sequence-search sensitivity and accuracy of the resulting sequence alignments. We present an open-source, general-purpose tool that represents both query and database sequences by profile hidden Markov models (HMMs): 'HMM-HMM based lightning-fast iterative sequence search' (HHblits; http://toolkit.genzentrum.lmu.de/hhblits/). Compared to the sequence-search tool PSI-BLAST, HHblits is faster owing to its discretized-profile prefilter, has 50-100% higher sensitivity and generates more accurate alignments.