Hampson, D. J. D.Sav, SinemTsang, H. H.2018-04-122018-04-122017-12http://hdl.handle.net/11693/37576Date of Conference: 6-9 Dec. 2016Conference name: IEEE Symposium Series on Computational Intelligence (SSCI), 2016RNA design is the inverse of RNA folding and it appears to be NP-hard. In RNA design, a secondary structure is given and the goal is to find a nucleotide sequence that will fold into this structure. To find such sequence(s) involves exploring the exponentially large sequence space. In literature, heuristic algorithms are the standard technique for tackling the RNA design. Heuristic algorithms enable effective and efficient exploration of the high-dimensional sequence-structure space when searching for candidates that fold into a given target structure. The main goal of this paper is to investigate the use of multi-objective criteria in SIMARD and Quality Pre-selection Strategy (QPS). The objectives that we optimize are Hamming distance (between designed structure and target structure) and thermodynamic free energy. We examine the different combinations of optimization criteria, and attempt to draw conclusions about the relationships between them. We find that energy is a poor primary objective but makes an excellent secondary objective. We also find that using multi-objective pre-selection produces viable solutions in far fewer steps than was previously possible with SIMARD. © 2016 IEEE.EnglishArtificial intelligenceBioinformaticsFree energyHamming distanceHeuristic algorithmsMultiobjective optimizationRNAHigh-dimensionalNucleotide sequencesOptimization criteriaPrimary objectiveSecondary structuresSequence structureThermodynamic free-energyViable solutionsOptimizationConference Paper10.1109/SSCI.2016.7850232