Adapting And Enhancing Hybrid Computational Methods For RNA Secondary Structure Prediction
The secondary structure of RNA with pseudoknots is widely utilized for tracing the RNA tertiary structure, which is a key to understanding the functions of the RNAs and their useful roles in developing drugs for viral diseases. Experimental methods for determining RNA tertiary structure are time con...
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| 主要作者: | |
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| 格式: | Thesis |
| 語言: | English |
| 出版: |
2011
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| 主題: | |
| 在線閱讀: | http://eprints.usm.my/43465/1/RA%E2%80%99ED%20MOHAMMAD%20ALI%20AL-KHATIB.pdf |
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| 總結: | The secondary structure of RNA with pseudoknots is widely utilized for tracing the RNA tertiary structure, which is a key to understanding the functions of the RNAs and their useful roles in developing drugs for viral diseases. Experimental methods for determining RNA tertiary structure are time consuming and tedious. Therefore, predictive computational approaches are required. Predicting the most accurate and energy-stable pseudoknot RNA secondary structure has been proven to be an NP-hard problem. This thesis presents a hybrid method to predict the RNA pseudoknot secondary structures by combining detection methods with dynamic programming algorithms. |
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