SIGffRid: A Tool for Identifying Sigma Factor Binding Sites in Bacterial Genomes
Author Information
Author(s): Touzain Fabrice, Schbath Sophie, Debled-Rennesson Isabelle, Aigle Bertrand, Kucherov Gregory, Leblond Pierre
Primary Institution: Laboratoire Lorrain de Recherche en Informatique et ses Applications
Hypothesis
The goal is to design an algorithm detecting sigma factor binding sites by using combinational and statistical constraints deduced from biological observations.
Conclusion
The approach combining statistical and biological criteria was successful in predicting sigma factor binding sites.
Supporting Evidence
- The method was validated by cross-checking with known sigma factor binding sites.
- SIGffRid identified 113 motifs for Streptomyces coelicolor and 65 for Streptomyces avermitilis.
- The algorithm can be applied to any bacterial species using general properties.
Takeaway
The study created a computer program that helps find important DNA sequences in bacteria that control gene activity.
Methodology
The algorithm uses a comparative approach to analyze pairs of promoter regions of orthologous genes and identifies over-represented patterns in whole genomes.
Limitations
The algorithm may not be able to find all sigma factor binding sites due to the variability of spacer lengths and the need for closely related species.
Digital Object Identifier (DOI)
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