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A further development of the QNAR model to predict the cellular uptake of nanoparticles by pancreatic cancer cells.

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第一作者： Feng,Luan

第一单位： College of Chemistry and Chemical Engineering, Yantai University, Yantai 264005, P. R. China. Electronic address: fluan@sina.com.

作者： Feng,Luan ^[1] ; Lili,Tang ^[2] ; Lihong,Zhang ^[2] ; Shuang,Zhang ^[2] ; Maykel Cruz,Monteagudo ^[3] ; M Natália D S,Cordeiro ^[4]

作者单位： College of Chemistry and Chemical Engineering, Yantai University, Yantai 264005, P. R. China. Electronic address: fluan@sina.com. ^[1] College of Chemistry and Chemical Engineering, Yantai University, Yantai 264005, P. R. China. ^[2] LAQV@REQUIMTE/Department of Chemistry and Biochemistry, Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal; CIQUP/Department of Chemistry and Biochemistry, Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal. ^[3] LAQV@REQUIMTE/Department of Chemistry and Biochemistry, Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal. Electronic address: ncordeir@fc.up.pt. ^[4]

关键词 Multiple linear regression method (MLR)Nanomaterials Quantitative Nanostructure–Activity relationship (QNAR)Radial basis function neural network (RBFNN)

医学主题词人类(Humans);模型, 生物学(Models, Biological);纳米粒子(Nanoparticles);胰腺肿瘤(Pancreatic Neoplasms);量化构效关系(Quantitative Structure-Activity Relationship)

DOI 10.1016/j.fct.2017.04.010

PMID 28412403

发布时间 2019-12-10

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