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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
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Fast batch searching for protein homology based on compression and clustering
Hongwei Ge1, Liang Sun2, Jinghong Yu1
1College of Computer Science and Technology, Dalian University of Technology, No.2, Linggong Road, Dalian, China.
BMC Bioinformatics
|November 23, 2017
Summary
We developed C2-BLASTP, an efficient algorithm for searching protein sequence homology. This method significantly improves speed and accuracy by compressing and clustering query sequences and databases, outperforming existing approaches.
Area of Science:
- Bioinformatics
- Computational Biology
- Genomics
Background:
- Protein sequence matching is crucial in bioinformatics.
- Current methods like BLAST are inefficient for multiple queries due to redundant computations.
- Common subsequences among queries are not effectively utilized.
Purpose of the Study:
- To develop a novel algorithm, C2-BLASTP, for efficient batch homology searching.
- To exploit joint information among query sequences and databases.
- To improve the speed, accuracy, and memory usage of sequence alignment.
Main Methods:
- Implemented a compression strategy involving redundancy analysis, removal, and distinction recording for queries and databases.
- Clustered the database based on Hamming distance of subsequences.
- Utilized reduced amino acid alphabets to enhance alignment sensitivity and selectivity.
- Developed an execution database from potential hits to manage large datasets.
- Performed homology search on the execution database.
Main Results:
- C2-BLASTP demonstrates effectiveness in batch homology searching on large datasets like NCBI NR.
- Evaluated performance based on homology accuracy, search speed, and memory consumption.
- Achieved competitive results compared to state-of-the-art methods.
Conclusions:
- C2-BLASTP offers a significant improvement over traditional methods for multiple sequence homology searches.
- The algorithm provides a more efficient and accurate approach to analyzing large-scale biological sequence data.
- C2-BLASTP represents a competitive advancement in bioinformatics sequence analysis tools.
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