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dc.contributor.author황승용-
dc.date.accessioned2018-03-12T02:40:50Z-
dc.date.available2018-03-12T02:40:50Z-
dc.date.issued2013-08-
dc.identifier.citationMOLECULAR & CELLULAR TOXICOLOGY, Aug 2013, 9(3), P.277-284en_US
dc.identifier.issn1738-642X-
dc.identifier.urihttps://link.springer.com/article/10.1007%2Fs13273-013-0035-y-
dc.identifier.urihttp://hdl.handle.net/20.500.11754/45172-
dc.description.abstractIn the industrial age, people are exposed to many hazardous substances in many ways. Generally, exposure is of low doses, but chronic symptoms are associated with many industrial pollutants, and therefore, early prediction of exposure is important. In this study, we intended to determine the reliability of the predictive modeling and biomarkers of a previous study, and to determine the related pathway of that biomarkers. We analyzed the key pathways and biological processes associated with volatile organic compounds (VOCs) from previous data - VOCs biomarker CRCT1, RUNX3, PCDH11X and PCSK6. In the analysis, inflammation and neoplasm were remarkably frequently occurring disease within the VOCs exposed body, and especially, exposure to toluene, presents a great likelihood of nerve disease or nervous system disease. Those diseases were related with the several biological processes, they are cell proliferation, apoptosis, inflammatory response, and nervous system development. This study shows probability that application of decision supporting systems, moreover it is helpful to decide whether VOCs exposure has occurred or not, and to predict negative effects.en_US
dc.description.sponsorshipThis subject was supported by the Korea Ministry of Environment as a "Converging technology project".en_US
dc.language.isoenen_US
dc.publisherTHE KOREAN SOCIETY OF TOXICOGENOMICS AND TOXICOPRPTEOMICSen_US
dc.subjectVolatile organic compoundsen_US
dc.subjectDecision supporting systemen_US
dc.subjectChemical exposure predictionen_US
dc.subjectPathwayen_US
dc.subjectBiological processen_US
dc.titlePrediction of VOCs based on functional analysis by decision supporting systemen_US
dc.typeArticleen_US
dc.relation.no3-
dc.relation.volume9-
dc.identifier.doi10.1007/s13273-013-0035-y-
dc.relation.page277-284-
dc.relation.journalMOLECULAR & CELLULAR TOXICOLOGY-
dc.contributor.googleauthorAn, Y. R.-
dc.contributor.googleauthorShin, G. H.-
dc.contributor.googleauthorKang, B. C.-
dc.contributor.googleauthorKim, S. J.-
dc.contributor.googleauthorYu, S. Y.-
dc.contributor.googleauthorYoon, H. J.-
dc.contributor.googleauthorHwang, S. Y.-
dc.relation.code2013006249-
dc.sector.campusS-
dc.sector.daehakGRADUATE SCHOOL[S]-
dc.sector.departmentDEPARTMENT OF BIONANOTECHNOLOGY-
dc.identifier.pidsyhwang-
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GRADUATE SCHOOL[S](대학원) > BIONANOTECHNOLOGY(바이오나노학과) > Articles
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