Abstract
Pseudoknots are special units in RNA structure. They are found in almost all categories of RNAs. Since the prediction of the pseudoknotted structure has been proven to be NP-complete, heuristic methods have been proposed to alleviate the issue of computational complexity. The Coincidence algorithm (COIN) was applied to predict the RNA secondary structure with pseudoknots. The proposed method relaxed some conditions to identify structures that contain pseudoknots, and also presented a new fitness function that combines approximate minimum free energy (MFE) and maximum expected accuracy (MEA). The new fitness function makes the algorithm faster than using standard MFE but still reflects the quality of the predictive structure. The proposed method was tested on the Pseudobase ++ database and compared with the PRSA based on Simulated Annealing (SA), IPknot, TT2NE, and RNAstructure. On average, the proposed method outperformed the other methods. It yields F1 scores 3 % to 24 % higher than the compared methods.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
