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Published on: August 20, 2014
A new approach for detecting riboswitches in DNA sequences
Jessen T Havill1, Chinmoy Bhatiya1, Steven M Johnson1
1Department of Mathematics and Computer Science, Department of Biology, Denison University, Granville, OH 43023, Capco, New York, NY, 10005, Department of Computer Science, Wake Forest University, Winston-Salem, NC 27109 and College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USA.
The Denison Riboswitch Detector (DRD) tool rapidly identifies potential riboswitches in bacterial genomes. This computational method offers high accuracy, aiding researchers in understanding gene expression regulation.
Area of Science:
- Bioinformatics
- Computational Biology
- Genomics
Background:
- Riboswitches are RNA sequences that regulate gene expression by altering their structure.
- Computational prediction of riboswitches aids molecular biologists in studying gene regulation.
Purpose of the Study:
- To introduce the Denison Riboswitch Detector (DRD), a novel computational tool for identifying riboswitches.
- To provide a user-friendly web interface for rapid riboswitch detection in large DNA sequences.
Main Methods:
- Developed a computational algorithm that models riboswitch detection as a 'heaviest path' problem on a multipartite graph.
- Utilized efficient dynamic programming to solve the graph problem.
- Implemented the algorithm in a web-accessible tool, DRD.
Main Results:
- The Denison Riboswitch Detector (DRD) can identify putative riboswitches in DNA sequences at the scale of bacterial genomes.
- DRD demonstrates high performance with approximately 88-99% sensitivity and over 99.99% specificity across 13 riboswitch families.
- The tool allows for easy modification and creation of riboswitch descriptions.
Conclusions:
- DRD is an effective and accurate computational tool for identifying riboswitches.
- The tool facilitates research into riboswitch-mediated gene expression regulation.
- DRD is accessible via a web interface for broad scientific use.
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