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...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Al-Khatib, Ra’ed Mohammad Ali
التنسيق: أطروحة
اللغة:English
منشور في: 2011
الموضوعات:
الوصول للمادة أونلاين:http://eprints.usm.my/43465/1/RA%E2%80%99ED%20MOHAMMAD%20ALI%20AL-KHATIB.pdf
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الوصف
الملخص: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.