The purpose of researching bacterial gene expression is to control and prevent the diseases which are caused by bacteria. Recently researchers discovered small non-coding RNAs (ncRNA / sRNA) perform a variety of critical regulatory functions in bacteria. The genome-wide searching for sRNAs, especially the computational method, has become an effective way to predict the small non-coding RNAs because sRNAs have the consistent sequence characteristics. This article proposes a hybrid computational approach, HybridRNA, for the prediction of small non-coding RNAs, which integrates three critical techniques, including secondary structural algorithm, thermo-dynamic stability analysis and sequence conservation prediction. Relying on these computational techniques, our approach was used to search for sRNAs in Streptococcus pyogenes which is one of the most important bacteria for human health. This search led five strongest candidates of sRNA to be predicted as the key components of known regulatory pathways in S. pyogens.
| Identifer | oai:union.ndltd.org:siu.edu/oai:opensiuc.lib.siu.edu:theses-1086 |
| Date | 01 December 2009 |
| Creators | Yu, Ning |
| Publisher | OpenSIUC |
| Source Sets | Southern Illinois University Carbondale |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses |
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