Investigation of multi-objective optimization criteria for RNA design

dc.citation.epage8
dc.citation.spage1
dc.contributor.authorHampson, D. J. D.en_US
dc.contributor.authorSav, Sinemen_US
dc.contributor.authorTsang, H. H.en_US
dc.coverage.spatialAthens, Greece
dc.date.accessioned2018-04-12T11:44:25Z
dc.date.available2018-04-12T11:44:25Z
dc.date.issued2017-12
dc.departmentDepartment of Computer Engineering
dc.descriptionDate of Conference: 6-9 Dec. 2016
dc.descriptionConference name: IEEE Symposium Series on Computational Intelligence (SSCI), 2016
dc.description.abstractRNA 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.
dc.identifier.doi10.1109/SSCI.2016.7850232
dc.identifier.urihttp://hdl.handle.net/11693/37576
dc.language.isoEnglish
dc.publisherIEEE
dc.relation.isversionofhttp://dx.doi.org/10.1109/SSCI.2016.7850232
dc.source.titleIEEE Symposium Series on Computational Intelligence, SSCI 2016
dc.subjectArtificial intelligence
dc.subjectBioinformatics
dc.subjectFree energy
dc.subjectHamming distance
dc.subjectHeuristic algorithms
dc.subjectMultiobjective optimization
dc.subjectRNA
dc.subjectHigh-dimensional
dc.subjectNucleotide sequences
dc.subjectOptimization criteria
dc.subjectPrimary objective
dc.subjectSecondary structures
dc.subjectSequence structure
dc.subjectThermodynamic free-energy
dc.subjectViable solutions
dc.subjectOptimization
dc.titleInvestigation of multi-objective optimization criteria for RNA design
dc.typeConference Paper

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