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HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment
Michael Remmert1, Andreas Biegert, Andreas Hauser
1Gene Center and Center for Integrated Protein Science Munich, Ludwig-Maximilians Universität München, Munich, Germany.
Nature Methods
|December 27, 2011
Summary
HHblits is a new tool for protein sequence analysis. It uses profile hidden Markov models (HMMs) for faster, more sensitive, and accurate protein function and structure prediction.
Area of Science:
- Bioinformatics
- Computational Biology
- Structural Biology
Background:
- Protein function and structure prediction are vital for biological research.
- Accurate sequence alignments are crucial for these predictions.
- Existing tools like PSI-BLAST have limitations in speed and sensitivity.
Purpose of the Study:
- To introduce HHblits, a novel tool for sequence-based protein analysis.
- To improve the sensitivity and accuracy of sequence alignments.
- To provide a faster alternative to existing sequence search tools.
Main Methods:
- Utilizing profile hidden Markov models (HMMs) for both query and database sequences.
- Implementing a discretized-profile prefilter for accelerated searching.
- Developing an iterative search strategy for enhanced accuracy.
Main Results:
- HHblits demonstrates significantly higher sensitivity (50-100%) compared to PSI-BLAST.
- HHblits generates more accurate sequence alignments.
- The tool offers a considerable speed improvement over PSI-BLAST.
Conclusions:
- HHblits represents a significant advancement in sequence-based protein function and structure prediction.
- The tool's speed, sensitivity, and accuracy make it valuable for biological research.
- HHblits is an open-source, general-purpose tool readily available to the scientific community.
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