Predicting RNA Secondary Structures Including Pseudoknots
نویسنده
چکیده
RNA secondary structures play a vital role in modern genetics and a lot of time and e ort has been put into their study. It is important to be able to predict them with high accuracy, since methods involving manual analysis are expensive, time-consuming and error-prone. Predictions can also be used to guide experiments to reduce time and money requirements. Several algorithms have been developed for implementing this task. Most of them assume that the desired secondary structure will not contain pseudoknots. However, pseudoknots, though not occurring that often, play an important role in a secondary structure as a whole. This report describes in detail the full thermodynamic model used to predict secondary structures without pseudoknots and the associated algorithm. It proceeds to extend the model to include a restricted class of pseudoknots and presents an e cient algorithm for the prediction of structures within this class. This algorithm has a running time complexity of O(n) and a spatial complexity of O(n), putting it on a high competitive edge with other known algorithms that take pseudoknots into account. A detailed discussion of implementation and an appendix containing the program code are also
منابع مشابه
RNA Secondary Structure Prediction Algorithms
RNA secondary structure prediction is an important problem studied extensively in the past three dacades. However, pseudoknots are usually excluded in RNA secondary structure prediction due to the hardness of examining all possible structures efficiently and model the energy correctly. Current algorithms on predicting structures with pseudoknots usually have extremely high resource requirements...
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