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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xiaolu Huang Ali, H. |
| Copyright Year | 2007 |
| Description | Author affiliation: Univ. of Nebraska at Omaha, Omaha (Xiaolu Huang; Ali, H.) |
| Abstract | Pseudoknots are important functional structures in RNA. Despite of numerous pseudoknot prediction tools, biologists still need a pseudoknot detection method with much higher sensitivity. We have previously developed the pseudoknot local motif model and dynamic partner sequence stacking (PLMMDPSS) algorithm which predicts short loop 2 pseudoknots with high sensitivity. Integrated with Mfold, PLMM_DPSS is capable of predicting both H-type and complicated type pseudoknots. In this study, we have developed PLMM_DPSS_SF Mfold_FF with the following modifications: the extension of the PLM model to include long loop 2 pseudoknots, the incorporation of overall folding energy calculation, recombination of non-overlapping pseudoknots within one sequence and two filters for higher specificity, The prediction results have shown that PLMM_DPSS_SF_Mfold_FF is more sensitive than other leading pseudoknot prediction tools and results in a low alternative folding number, and results also support the notion that some kinetic barriers may trap RNA folding in local minimums. |
| Starting Page | 1299 |
| Ending Page | 1303 |
| File Size | 1895792 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424415090 |
| DOI | 10.1109/BIBE.2007.4375735 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-10-14 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Filters RNA Predictive models Computer science Stacking Prediction algorithms Kinetic theory Iterative algorithms Biological system modeling Tree data structures filter PLMM_DPSS algorithm pseudoknot prediction |
| Content Type | Text |
| Resource Type | Article |
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