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Natural sequence code representations for compression and rapid searching of human-genome style databases
1Department of Molecular Biology, University of Manchester, UK.
Computer Applications in the Biosciences : CABIOS
|June 1, 1992
Summary
New bio-informatic codes for amino acid residues aid in comparing large gene and protein sequences. These natural codes enhance data searching and compression, offering significant speed improvements.
Area of Science:
- Bioinformatics
- Computational Biology
- Genomics
Background:
- Handling vast amounts of genetic and protein sequence data presents significant computational challenges.
- Existing methods for sequence analysis may not fully leverage the inherent properties of amino acids.
Purpose of the Study:
- To develop novel numeric descriptions (bio-informatic codes) for amino acid residues.
- To enhance the comparison, manipulation, storage, and searching of large-scale sequence data.
Main Methods:
- Creation of natural numeric codes based on amino acid properties.
- Integration of these codes with existing fast-search algorithms.
- Development of compressed databases using property-based residue classification.
Main Results:
- Demonstrated advantages in storing and searching large sequence datasets.
- Achieved data compression by defining residues based on properties (e.g., polar/non-polar).
- Preliminary studies indicated up to a 4.5-fold speed increase in data processing.
Conclusions:
- The developed bio-informatic codes offer a natural and efficient way to represent amino acid residues.
- These codes facilitate improved data compression and faster searching of genomic and proteomic databases.
- Coding extensions can imbue sequence data with advanced computational characteristics for more intelligent analysis.