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Bridges: a tool for identifying local similarities in long sequences
Alexey S Kondrashov1, Raquel Assis
1Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA. kondrash@umich.edu
Bioinformatics (Oxford, England)
|June 22, 2010
Summary
Bridges is a heuristic search tool for identifying sequence similarities. This tool efficiently compares large genome datasets in a single run, offering adjustable sensitivity and specificity through 20 parameters.
Area of Science:
- Bioinformatics
- Computational Biology
- Genomics
Background:
- Bridges is a heuristic search tool developed using the C programming language.
- It is compatible with all platforms and its source code is publicly available.
- Documentation and source code can be accessed at http://github.com/rassis/bridges.
Purpose of the Study:
- To introduce Bridges, a novel heuristic search tool for sequence similarity identification.
- To describe the stages and capabilities of the Bridges tool for efficient data analysis.
Main Methods:
- Bridges employs short word matches to detect local similarities within sequences.
- The tool operates in three distinct stages: filtering input sequences, identifying local similarities, and post-processing these similarities.
- Input sequence data is released from memory post-filtering, enabling efficient comparison of genome-scale datasets.
Main Results:
- Bridges facilitates rapid identification of local similarities between biological sequences.
- The tool's architecture allows for efficient, single-run comparisons of large genome-scale datasets.
- Users can customize search sensitivity and specificity using 20 adjustable parameters.
Conclusions:
- Bridges is an effective heuristic search tool for rapid local sequence similarity identification.
- Its design enables efficient genome-scale data comparison in a single run.
- The tool offers flexibility through user-adjustable parameters for tailored search performance.
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