Publication:
Comparison of CpG island distribution in human neuron- and myocyte-specific genes with housekeeping genes using bioinformatics and artificial neural networks

dc.contributor.authorPermphan Dharmasarojaen_US
dc.contributor.otherMahidol Universityen_US
dc.date.accessioned2018-05-03T08:08:47Z
dc.date.available2018-05-03T08:08:47Z
dc.date.issued2011-10-06en_US
dc.description.abstractCpG islands are cluster of CG-rich DNA sequences that associate with the promoter of many human genes. Previous studies based on the original CpG criteria, as being length > 200 bp, %GC ≥ 50%, and ObsCpG/ExpCpG ≥ 0.60, showed that CpG islands overlap the promoter of all human housekeeping genes and over half of all tissue-specific genes. The present study, using the new and widely accepted criteria defined as length > 500 bp, %GC ≥ 55%, and ObsCpG/ExpCpG ≥ 0.65, showed that CpG islands of ∼60% of housekeeping genes overlap the promoter, suggesting that the previous studies might include Alu repeats in the promoter region. Using artificial neural networks, RBF, MLP, PNN, and SVM identified ObsCpG/ExpCpG of the 5′ region-CpG islands and ratio of exonic CpG island number to total CpGs as important variables for classification of myocytes-specificity, with ObsCpG/ExpCpG < 0.65 being specific. For classification of neuron-specificity, the %GC and ObsCpG/ExpCpG of the 5′ region-CpG islands were important variables. © 2011 IEEE.en_US
dc.identifier.citationProceedings - 2011 7th International Conference on Natural Computation, ICNC 2011. Vol.1, (2011), 556-560en_US
dc.identifier.doi10.1109/ICNC.2011.6022068en_US
dc.identifier.other2-s2.0-80053408123en_US
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/123456789/11769
dc.rightsMahidol Universityen_US
dc.rights.holderSCOPUSen_US
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=80053408123&origin=inwarden_US
dc.subjectComputer Scienceen_US
dc.subjectNeuroscienceen_US
dc.titleComparison of CpG island distribution in human neuron- and myocyte-specific genes with housekeeping genes using bioinformatics and artificial neural networksen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=80053408123&origin=inwarden_US

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