Chan, Tak-MingTak-MingChanLo, Leung-YauLeung-YauLoWong, Man-LeungMan-LeungWongLiang, YongYongLiangProf. LEUNG Kwong Sak2023-03-162023-03-1620132013 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), 2013, pp. 198-2059781467358750http://hdl.handle.net/20.500.11861/7508DNA motif discovery is an important problem for deciphering protein-DNA bindings in gene regulation. To discover generic spaced motifs which have multiple conserved patterns separated by wild-cards called spacers, the genetic algorithm (GA) based GASMEN has been proposed and shown to outperform related methods. However, the over-generic modeling of any number of spacers increases the optimization difficulty in practice. In protein-DNA binding case studies, complicated spaced motifs are rare while dimers with single spacers are more common spaced motifs. Moreover, errors (mismatches) in a conserved pattern are not arbitrarily distributed as certain highly conserved nucleotides are essential to maintain bindings. Motivated by better optimization in real applications, we have developed a new method, which is GA for Dimer-led and Error-restricted Spaced Motifs (GADESM). Common spaced motifs are paid special attention to using dimer-led initialization in the population initialization. The results on real datasets show that the dimer-led initialization in GADESM achieves better fitness than GASMEN with statistical significance. With additional error-restricted motif occurrence retrieval, GADESM has shown better performance than GASMEN on both comprehensive simulation data and a real ChIP-seq case study.enMotif DiscoverySimulated DataReal ApplicationsCommon MotifMotif OccurrencesComprehensive SimulationGeneral MotifFalse PositiveDimerizationEvaluation Of FunctionSimulation ExperimentsTranscription Factor Binding SitesSimulated DatasetsPosition ErrorPosition Weight MatricesReverse ComplementEstrogen Response ElementsHamming DistanceSubstringGenetic OperatorsPalindromic MotifDimerization MotifSubstitution ErrorsCore BindingPerformance Evaluation MetricsTotal PenaltyReal Data ApplicationFitness Score3D StructureMotif WidthConference Paper10.1109/CIBCB.2013.6595409