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- W2153144410 abstract "This work explores a new approach in using genetic algorithm to predict RNA secondary structures with pseudoknots. Since only a small portion of most RNA structures is comprised of pseudoknots, the majority of structural elements from an optimal pseudoknot-free structure are likely to be part of the true structure. Thus seeding the genetic algorithm with optimal pseudoknot-free structures will more likely lead it to the true structure than a randomly generated population. The genetic algorithm uses the known energy models with an additional augmentation to allow complex pseudoknots. The nearest-neighbor energy model is used in conjunction with Turner’s thermodynamic parameters for pseudoknot-free structures, and the H-type pseudoknot energy estimation for simple pseudoknots. Testing with known pseudoknot sequences from PseudoBase shows that it out performs some of the current popular algorithms. Table of" @default.
- W2153144410 created "2016-06-24" @default.
- W2153144410 creator A5050079376 @default.
- W2153144410 date "2019-04-18" @default.
- W2153144410 modified "2023-09-26" @default.
- W2153144410 title "A Seeded Genetic Algorithm for RNA Secondary Structural Prediction with Pseudoknots" @default.
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- W2153144410 doi "https://doi.org/10.31979/etd.tn97-fmrj" @default.
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