期刊
NATURE METHODS
卷 9, 期 2, 页码 173-175出版社
NATURE PUBLISHING GROUP
DOI: 10.1038/NMETH.1818
关键词
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资金
- Deutsche Forschungsgemeinschaft [SFB646]
- Ludwig-Maximilians Universitat Munich through Excellence Initiative of the Bundesministerium fur Bildung und Forschung
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.
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