Study on Screening of Cigarette Smoke Exposure Biomarkers for Rat′s Metabolites on the Basis of Artificial Intelligence Technologies
  
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KeyWord:artificial neural networks  neurofuzzy logic  metabolomics  cigarette smoke exposure  key biomarkers
  
AuthorInstitution
XIE Yuan-yuan,SU Jia-kun,YING Xu-hui,LUO Juan-min,WANG Yi-ming,SHAO Deng-yin,LUO Guo-an,CAI Ji-bao 1.清华大学化学系;2.江西中烟工业有限责任公司;3.珠海清大弘瑞生物科技有限公司
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Abstract:
      Multivariate statistical analysis methods,principal component analysis and partial least square discrimination analysis,were applied in this study for the data mining of cigarette smoke exposure metabolomics on plasma,urine and lung samples,in order to characterize the holistic influences of cigarette smoke exposure,and screen potential biomarkers.The screened biomarkers obtained from the metabolic profiling analysis on plasma,urine and lung were integrated and reduced by neurofuzzy logic.The predictability of the established model with this focused biomarkers were evaluated by artificial neural networks.Key biomarkers were closely related to different smoke exposure time(7,14,30 days),and different kinds of cigarette smoke exposure on the endogenous metabolites in rats were found in this study,and the damage mechanism of cigarette smoke exposure on rat′s organism was discussed.
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