title: [Sort similarity based on computational method for chemical fingerprinting].
abstract: The key parts of chemical fingerprinting. However, the performance of the current whole similarity determining method sometimes is inadequate when the chromatograms of different classes are similar. The present study was focused on developing a sort similarity measure determining method for these problems. In this method, chemical fingerprint features are extracted from original chromatograms for classifying the samples. Further, the fluctuations of chemical compositions among the same class samples are evaluated using an inter-class similarity measure. The proposed method was applied to evaluate the quality of Sarcandra glabra samples through their HPLC fingerprints. The results showed that the different parts of this plant, i.e., the aerial and the whole, were clearly classified, and chemical fluctuations of samples with the same sort were well represented.
authors.affiliation: Pharmaceutical Informatics Institute, Zhejiang University, Hangzhou 310058, China.
authors.forename: Jinghua
authors.initials: J
authors.lastname: Zhong
authors.forename: Xiaorong
authors.initials: X
authors.lastname: Hou
authors.forename: Xiaohui
authors.initials: X
authors.lastname: Fan
mesh_terms: D002845:Chromatography / Q000379:methods*; D002851:Chromatography, High Pressure Liquid / Q000379:methods*; D019684:Magnoliopsida / Q000737:chemistry*; D010936:Plant Extracts / Q000032:analysis*
chemical_list: D010936:Plant Extracts