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Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group
Published on: August 16, 2017
A new approach for alignment of multiple proteins
1Department of Computer and Information Sciences and Engineering, University of Florida, Gainesville, FL 32611, USA. xuzhang@cise.ufl.edu
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
|November 11, 2006
Summary
We developed Horizontal Sequence Alignment (HSA), a novel graph-based method for protein sequence alignment. HSA outperforms existing tools, especially for low-similarity proteins, by considering all sequences simultaneously.
Area of Science:
- Bioinformatics
- Computational Biology
- Structural Bioinformatics
Background:
- Multiple sequence alignment (MSA) is crucial for understanding protein evolution and function.
- Existing progressive alignment methods suffer from order-dependency, potentially leading to suboptimal results.
- Accurate MSA is challenging, particularly for protein families with low sequence similarity.
Purpose of the Study:
- To introduce a novel graph-based multiple sequence alignment method called Horizontal Sequence Alignment (HSA).
- To address the limitations of order-dependent progressive alignment methods.
- To improve the accuracy and biological relevance of protein sequence alignments, especially for divergent sequences.
Main Methods:
- Developed HSA, a graph-based approach that processes all protein sequences simultaneously.
- HSA utilizes a sliding window technique across sequences.
- Incorporated secondary structure information alongside amino acid sequences for biologically relevant alignments.
Main Results:
- HSA demonstrates higher accuracy than existing multiple sequence alignment tools on BAliBASE benchmarks.
- The method shows significant improvements for aligning protein sequences with low similarity.
- HSA's simultaneous consideration of all sequences overcomes the order-dependency issue.
Conclusions:
- HSA offers a more accurate and robust approach to multiple sequence alignment.
- The method's ability to integrate structural information enhances alignment quality.
- HSA is particularly beneficial for analyzing distantly related protein sequences.
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