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个人信息Personal Information
教授
博士生导师
硕士生导师
性别：女
毕业院校：大连理工大学
学位：博士
所在单位：计算机科学与技术学院
电子邮箱：datas@dlut.edu.cn
Classification and differential metabolite discovery of liver diseases based on plasma metabolic profiling and support vector machines
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论文类型：期刊论文
发表时间：2011-11-01
发表刊物：JOURNAL OF SEPARATION SCIENCE
收录刊物：Scopus、SCIE、EI、PubMed
卷号：34
期号：21
页面范围：3029-3036
ISSN号：1615-9306
关键字：Analysis of variance; GC-MS; Liver diseases; Metabonomics; Support vector machine
摘要：Discovery of differential metabolites is the focus of metabonomics study. It has very important applications in pathogenesis and disease classification. The aim of this work is to identify differential metabolites for classifying the patients with hepatocellular carcinoma, cirrhosis and hepatitis based on metabolic profiling data analyzed by gas chromatography-time of flight mass spectrometry. A two-stage feature selection algorithm, F-SVM, combining F-score in analysis of variance and support vector machine (SVM), was applied in discovering discriminative metabolites for three different types of liver diseases. The results show that the accuracy rate of the double cross-validation was 73.68 +/- 2.98%. 22 important differential metabolites selected by F-SVM were identified and related pathophysiological process of liver diseases was set forth. We conclude that F-SVM is quite feasible to be applied in the selection of biologically relevant features in metabonomics.
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