Investigation of multi-objective optimization criteria for RNA design

dc.citation.epage8en_US
dc.citation.spage1en_US
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.issued2017-12en_US
dc.departmentDepartment of Computer Engineeringen_US
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.en_US
dc.description.provenanceMade available in DSpace on 2018-04-12T11:44:25Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 179475 bytes, checksum: ea0bedeb05ac9ccfb983c327e155f0c2 (MD5) Previous issue date: 2017en
dc.identifier.doi10.1109/SSCI.2016.7850232en_US
dc.identifier.urihttp://hdl.handle.net/11693/37576en_US
dc.language.isoEnglishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/SSCI.2016.7850232en_US
dc.source.titleIEEE Symposium Series on Computational Intelligence, SSCI 2016en_US
dc.subjectArtificial intelligenceen_US
dc.subjectBioinformaticsen_US
dc.subjectFree energyen_US
dc.subjectHamming distanceen_US
dc.subjectHeuristic algorithmsen_US
dc.subjectMultiobjective optimizationen_US
dc.subjectRNAen_US
dc.subjectHigh-dimensionalen_US
dc.subjectNucleotide sequencesen_US
dc.subjectOptimization criteriaen_US
dc.subjectPrimary objectiveen_US
dc.subjectSecondary structuresen_US
dc.subjectSequence structureen_US
dc.subjectThermodynamic free-energyen_US
dc.subjectViable solutionsen_US
dc.subjectOptimizationen_US
dc.titleInvestigation of multi-objective optimization criteria for RNA designen_US
dc.typeConference Paperen_US

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