林晓惠

基本信息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

在职信息 : 在职

所在单位 : 计算机科学与技术学院

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个人简介Personal Profile

大连理工大学计算机科学与技术学院,教授,博士生导师。主要研究方向为机器学习、数据挖掘、生物信息处理。
近年发表的主要文章:
1. Xin Huang, Jun Zeng, et al. A new strategy for analyzing time-series data using dynamic networks: identifying prospective biomarkers of hepatocellular carcinoma. Scientific Reports, 2016, 6: 32448.
2. Weijian Zhang, Lina Zhou, et al. A weighted relative difference accumulation algorithm for dynamic metabolomics data: long-term elevated serum bile acids are risk factors for hepatocellular carcinoma. Scientific Reports, 2015, 5: 8984.
3. Jun Zeng, Xin Huang, et al. Metabolomics identifies biomarker pattern for early diagnosis of hepatocellular carcinoma: from Diethylnitrosamine treated rats to patients, Scientific Reports, 5: 16101.
4. Xiaohui Lin, Jiuchong Gao, et al. A modified k-TSP algorithm and its application in LC-MS-based metabolomics study of hepatocellular carcinoma and chronic liver diseases. Journal of Chromatography B, 2014, 966: 100-108.
5. Xiaohui Lin, Fufang Yang, et al. A support vector machine-recursive feature elimination feature selection method based on artificial contrast variables and mutual information, Journal of Chromatography B. 2012, 910: 149-155.
6. 林晓惠,明迪,等. MS-IAS: 集成的质谱代谢组学数据分析系统. 分析化学,2012,40(9): 1366-1373.
7. Xiaohui Lin, Quancai Wang, et al. A method for handling metabonomics data from liquid chromatography/mass spectrometry: combinational use of support vector machine recursive feature elimination, genetic algorithm and random forest for feature selection. Metabolomics, 2011, 7(4): 549-558.
8. Jing Chen, Yang Zhang, et al. Application of L-EDA in metabonomics data handling: global metabolite profiling and potential biomarker discovery of epithelial ovarian cancer prognosis. Metabolomics, 2011, 7(4):614-622.
9. Xiaohui Lin, Yang Zhang, et al. Classification and differential metabolite discovery of liver diseases based on plasma metabolic profiling and support vector machines. Journal of Separation Science, 2011, 34(21): 3029-3036.

  • 教育经历Education Background
  • 工作经历Work Experience
  • 研究方向Research Focus
  • 社会兼职Social Affiliations
  • 机器学习,数据挖掘。