SIMARD: a simulated annealing based RNA design algorithm with quality pre-selection strategies

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dc.citation.epage8en_US
dc.citation.spage1en_US
dc.contributor.authorSav, Sinemen_US
dc.contributor.authorHampson, D. J. D.en_US
dc.contributor.authorTsang, H. H.en_US
dc.coverage.spatialAthens, Greece
dc.date.accessioned2018-04-12T11:44:26Z
dc.date.available2018-04-12T11:44:26Z
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.abstractMost of the biological processes including expression levels of genes and translation of DNA to produce proteins within cells depend on RNA sequences, and the structure of the RNA plays vital role for its function. RNA design problem refers to the design of an RNA sequence that folds into given secondary structure. However, vast number of possible nucleotide combinations make this an NP-Hard problem. To solve the RNA design problem, a number of researchers have tried to implement algorithms using local stochastic search, context-free grammars, global sampling or evolutionary programming approaches. In this paper, we examine SIMARD, an RNA design algorithm that implements simulated annealing techniques. We also propose QPS, a mutation operator for SIMARD that pre-selects high quality sequences. Furthermore, we present experiment results of SIMARD compared to eight other RNA design algorithms using the Rfam datset. The experiment results indicate that SIMARD shows promising results in terms of Hamming distance between designed sequence and the target structure, and outperforms ERD in terms of free energy. © 2016 IEEE.en_US
dc.identifier.doi10.1109/SSCI.2016.7849957en_US
dc.identifier.urihttp://hdl.handle.net/11693/37577
dc.language.isoEnglishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/SSCI.2016.7849957en_US
dc.source.titleIEEE Symposium Series on Computational Intelligence, SSCI 2016en_US
dc.subjectArtificial intelligenceen_US
dc.subjectComputational complexityen_US
dc.subjectComputer programmingen_US
dc.subjectContext free grammarsen_US
dc.subjectDNA sequencesen_US
dc.subjectFree energyen_US
dc.subjectGene expressionen_US
dc.subjectHamming distanceen_US
dc.subjectNucleic acidsen_US
dc.subjectProblem solvingen_US
dc.subjectRNAen_US
dc.subjectSimulated annealingen_US
dc.subjectStochastic systemsen_US
dc.subjectBiological processen_US
dc.subjectEvolutionary programming approachen_US
dc.subjectExpression levelsen_US
dc.subjectHigh-quality sequencesen_US
dc.subjectLocal stochastic searchesen_US
dc.subjectMutation operatorsen_US
dc.subjectSecondary structuresen_US
dc.subjectSimulated annealing techniquesen_US
dc.subjectBioinformaticsen_US
dc.titleSIMARD: a simulated annealing based RNA design algorithm with quality pre-selection strategiesen_US
dc.typeConference Paperen_US

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