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Published on: February 11, 2019
Evolutionary computation for discovery of composite transcription factor binding sites
Gary B Fogel1, V William Porto, Gabor Varga
1Natural Selection, Inc, San Diego, CA 92121, USA.
Nucleic Acids Research
|October 18, 2008
Summary
This study refines evolutionary computation to identify composite transcription factor binding sites (TFBS). The improved algorithm successfully detects complex TFBS, enhancing TFBS discovery for coexpressed genes.
Area of Science:
- Computational biology
- Genomics
- Bioinformatics
Background:
- Evolutionary computation has been used to discover transcription factor binding sites (TFBS).
- The ability of these methods to identify composite TFBS, crucial in higher organisms, was previously unclear.
Purpose of the Study:
- To refine an evolutionary computation algorithm for identifying composite TFBS.
- To test the algorithm's efficacy in detecting known composite elements like NFAT/AP-1.
Main Methods:
- Algorithm refinement included optimizing window size, implementing novel scoring methods (central bonusing), and self-adaptation for evolutionary operators.
- The NFAT/AP-1 complex was used as a case study to validate the approach.
Main Results:
- The improved algorithm successfully identified TFBS of varying sizes and complexity as top solutions.
- Some identified solutions showed known experimental links to NFAT/AP-1.
- Window size selection significantly impacts algorithm performance, even with tuned parameters.
Conclusions:
- The refined evolutionary computation algorithm effectively identifies composite TFBS.
- This enhanced approach promises to significantly improve the discovery of transcription factor binding sites.
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