Qfold: a new modeling paradigm for the RNA folding problem
Ribonucleic acid (RNA) molecules play informational, structural, and metabolic roles in all living cells. RNAs are chains of nucleotides containing bases {A, C, G, U} that interact via base pairings to determine higher order structure and functionality. The RNA folding problem is to predict one or m...
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| Published in: | Journal of heuristics Vol. 27; no. 4; pp. 695 - 717 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
New York
Springer US
01.08.2021
Springer Nature B.V |
| Subjects: | |
| ISSN: | 1381-1231, 1572-9397 |
| Online Access: | Get full text |
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| Summary: | Ribonucleic acid (RNA) molecules play informational, structural, and metabolic roles in all living cells. RNAs are chains of nucleotides containing bases {A, C, G, U} that interact via base pairings to determine higher order structure and functionality. The RNA folding problem is to predict one or more secondary RNA structures from a given primary sequence of bases. From a mathematical modeling perspective, solutions to the RNA folding problem come from minimizing the thermodynamic free energy of a structure by selecting which bases will be paired, subject to a set of constraints. Here we report on a Quadratic Unconstrained Binary Optimization (QUBO) modeling paradigm that fits naturally with the parameters and constraints required for RNA folding prediction. Three QUBO models are presented along with a hybrid metaheuristic algorithm. Extensive testing results show a strong positive correlation with benchmark results. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 1381-1231 1572-9397 |
| DOI: | 10.1007/s10732-021-09471-3 |