• 姓名: 许青松
  • 职称: 教授
  • 学位: 博士
  • 中南大学
  • 数学与统计学院
教育背景

1982.6: 获合肥工业大学工学学士学位;

1989.6: 获湖南大学理学硕士学位;

2001.6: 获湖南大学理学博士学位.

工作经历

1987年7月-89年1月: 任湖南大学数学系助教;

1989年2月-99年1月:任湖南大学数学系讲师;

1999年1月-99年4月:香港浸会大学统计学咨询与研究中心访问;

1999年4月-2002年4月: 任湖南大学数学系副教授

2002年5月-2004年8月:获欧盟发展项目资助,于布鲁塞尔自由大学药学院进行博士后研究;

2010年7月-2010年10月:香港理工大学应用生化系访问;

2004年9月--至今:任中南大学数学科学与计算技术学院教授。

教授课程
高等数学; 应用统计; 回归分析;统计学习及数据挖掘原理
科研项目

1.分析化学中数据发掘的化学计量学新方法研究, 国家自然科学基金;

2.高维数据的多元分辨法及其在中草药分析中的应用研, 国家自然科学基金;

3. 化学计量学中高维数据的统计学习方法, 国家自然科学基金;

4.化学数据的统计学习, 教育部留学回国科研启动基金;

5. 统计学习在化学数据挖掘的应用, 中国博士后科学基金;

6.系统生物学中组学数据分析的若干问题研究, 国家自然科学基金 2013-2016;

7.基于代谢组学的2型糖尿病高危人群风险评估方法研究, 国家自然科学基金 2012-2014。

论文专著

1. Y.-H. Yun, D.-S. Cao, M.-L. Tan, J. Yan, D.-B. Ren, Q.-S. Xu, L. Yu and Y.-Z. Liang (2014). "A simple idea on applying large regression coefficient to improve the genetic algorithm-PLS for variable selection in multivariate calibration." Chemometrics and Intelligent Laboratory Systems 130: 76-83.

2. Y.-H. Yun, W.-T. Wang, M.-L. Tan, Y.-Z. Liang, H.-D. Li, D.-S. Cao, H.-M. Lu and Q.-S. Xu (2014). "A strategy that iteratively retains informative variables for selecting optimal variable subset in multivariate calibration." Analytica chimica acta 807: 36-43.

3. Y.-H. Yun, Y.-Z. Liang, G.-X. Xie, H.-D. Li, D.-S. Cao and Q.-S. Xu (2013). "A perspective demonstration on the importance of variable selection in inverse calibration for complex analytical systems." Analyst 138(21): 6412-6421.

4. D.-S. Cao, Y.-Z. Liang, Z. Deng, Q.-N. Hu, M. He, Q.-S. Xu, G.-H. Zhou, L.-X. Zhang, Z.-x. Deng and S. Liu (2013). "Genome-scale screening of drug-target associations relevant to Ki using a chemogenomics approach." PloS one 8(4): e57680.

5. D.-S. Cao, Y.-Z. Liang, J. Yan, G.-S. Tan, Q.-S. Xu and S. Liu (2013). "PyDPI: Freely Available Python Package for Chemoinformatics, Bioinformatics, and Chemogenomics Studies." Journal of chemical information and modeling 53(11): 3086-3096.

6. D.-S. Cao, Q.-S. Xu, Q.-N. Hu and Y.-Z. Liang (2013). "ChemoPy: freely available python package for computational biology and chemoinformatics." Bioinformatics: btt105.

7. D.-S. Cao, Q.-S. Xu and Y.-Z. Liang (2013). "propy: a tool to generate various modes of Chou’s PseAAC." Bioinformatics 29(7): 960-962.

8. H.-D. Li, Y.-Z. Liang, X.-X. Long, Y.-H. Yun and Q.-S. Xu (2013). "The continuity of sample complexity and its relationship to multivariate calibration: A general perspective on first-order calibration of spectral data in analytical chemistry." Chemometrics and Intelligent Laboratory Systems 122: 23-30.

9. D.-S. Cao, G.-H. Zhou, S. Liu, L.-X. Zhang, Q.-S. Xu, M. He and Y.-Z. Liang (2013). "Large-scale prediction of human kinase–inhibitor interactions using protein sequences and molecular topological structures." Analytica chimica acta 792: 10-18.

10. X.-X. Long, H.-D. Li, W. Fan, Q.-S. Xu and Y.-Z. Liang (2013). "A model population analysis method for variable selection based on mutual information." Chemometrics and Intelligent Laboratory Systems 121: 75-81.

11. J. Yan, H. J.Huang, M. He, H. B. Lu, R. Yang, B. Kong, Q. S. Xu and Y. Z. Liang (2013). "Prediction of retention indices for frequently reported compounds of plant essential oils using multiple linear regression, partial least squares, and support vector machine." Journal of separation science 36(15): 2464-2471.

12. Y.-H. Yun, H.-D. Li, L. R. E Wood, W. Fan, J.-J. Wang, D.-S. Cao, Q.-S. Xu and Y.-Z. Liang (2013). "An efficient method of wavelength interval selection based on random frog for multivariate spectral calibration." Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 111: 31-36.

13. D.-S. Cao, J.-H. Huang, J. Yan, L.-X. Zhang, Q.-N. Hu, Q.-S. Xu and Y.-Z. Liang (2012). "Kernel< i> k-nearest neighbor algorithm as a flexible SAR modeling tool." Chemometrics and Intelligent Laboratory Systems 114: 19-23.

14. D.-S. Cao, S. Liu, Q.-S. Xu, H.-M. Lu, J.-H. Huang, Q.-N. Hu and Y.-Z. Liang (2012). "Large-scale prediction of drug–target interactions using protein sequences and drug topological structures." Analytica chimica acta 752: 1-10.

15. D.-S. Cao, Q.-S. Xu, L.-X. Zhang, J.-H. Huang and Y.-Z. Liang (2012). "Tree-based ensemble methods and their applications in analytical chemistry." TrAC Trends in Analytical Chemistry 40: 158-167.

16. D.-S. Cao, J.-C. Zhao, Y.-N. Yang, C.-X. Zhao, J. Yan, S. Liu, Q.-N. Hu, Q.-S. Xu and Y.-Z. Liang (2012). "In silico toxicity prediction by support vector machine and SMILES representation-based string kernel." SAR and QSAR in Environmental Research 23(1-2): 141-153.

17. G.-H. Fu, and Q.-S. Xu (2012). "Grouping variable selection by weight fused elastic net for multi-collinear data." Communications in Statistics-Simulation and Computation 41(2): 205-221.

18. J.-H. Huang, D.-S. Cao, J. Yan, Q.-S. Xu, Q.-N. Hu and Y.-Z. Liang (2012). "Using core hydrophobicity to identify phosphorylation sites of human G protein-coupled receptors." Biochimie 94(8): 1697-1704.

19. X. Huang, D. S. Cao, Q. S. Xu and Y. Z. Liang (2013). "A novel tree kernel partial least squares for modeling the structure–activity relationship." Journal of Chemometrics 27(3-4): 43-49.

20. X. Huang, D.-S. Cao, Q.-S. Xu, L. Shen, J.-H. Huang and Y.-Z. Liang (2013). "A novel tree kernel support vector machine classifier for modeling the relationship between bioactivity and molecular descriptors." Chemometrics and Intelligent Laboratory Systems 120: 71-76.

21. X. Huang, Q.-S. Xu and Y.-Z. Liang (2012). "PLS regression based on sure independence screening for multivariate calibration." Analytical Methods 4(9): 2815-2821.

22. H.-D. Li, Y.-Z. Liang, D.-S. Cao and Q.-S. Xu (2012). "Model-population analysis and its applications in chemical and biological modeling." TrAC Trends in Analytical Chemistry 38: 154-162.

23. H.-D. Li, Q.-S. Xu and Y.-Z. Liang (2012). "Random frog: an efficient reversible jump Markov chain Monte Carlo-like approach for variable selection with applications to gene selection and disease classification." Analytica chimica acta 740: 20-26.

24. H.-D. Li, Q.-S. Xu, W. Zhang and Y.-Z. Liang (2012). "Variable complementary network: a novel approach for identifying biomarkers and their mutual associations." Metabolomics 8(6): 1218-1226.

25. Z. Li, D.-J. Zhan, J.-J. Wang, J. Huang, Q.-S. Xu, Z.-M. Zhang, Y.-B. Zheng, Y.-Z. Liang and H. Wang (2013). "Morphological weighted penalized least squares for background correction." Analyst 138(16): 4483-4492.

26. J. Yan, D.-S. Cao, F.-Q. Guo, L.-X. Zhang, M. He, J.-H. Huang, Q.-S. Xu and Y.-Z. Liang (2012). "Comparison of quantitative structure–retention relationship models on four stationary phases with different polarity for a diverse set of flavor compounds." Journal of Chromatography A 1223: 118-125.

27. H.-D. Li, Y.-Z. Liang, Q.-S. Xu, D.-S. Cao, B.-B. Tan, B.-C. Deng, C.-C. Lin, Recipe for Uncovering Predictive Genes Using Support Vector Machines Based on Model Population Analysis. Ieee-Acm Transactions on Computational Biology and Bioinformatics 2011, 8(6), 1633-1641.

28. D.-S. Cao, Y.-Z. Liang, Q.-S. Xu, Q.-N. Hu, L.-X. Zhang, G.-H Fu, Exploring nonlinear relationships in chemical data using kernel-based methods. Chemometrics and Intelligent Laboratory Systems 2011, 107(1), 106-115.

29. D.-S. Cao, Y.-Z. Liang, Q.-S. Xu, L.-X. Zhang, Q.-N. Hu, H.-D. Li, Feature importance sampling-based adaptive random forest as a useful tool to screen underlying lead compounds. Journal of Chemometrics 2011, 25(4), 201-207.

30. G. H. Fu, Q. S Xu, H. D. Li, D. S. Cao, Y. Z. Liang, Elastic Net Grouping Variable Selection Combined with Partial Least Squares Regression (EN-PLSR) for the Analysis of Strongly Multi-collinear Spectroscopic Data. Applied Spectroscopy 2011, 65. 402-408.

31. D.-S. Cao, Y.-Z. Liang, Q.-S. Xu, Y.-F. Yun, H.-D. Li, Toward better QSAR/QSPR modeling: simultaneous outlier detection and variable selection using distribution of model features. Journal of Computer-Aided Molecular Design 2011, 25. 67-80.

32. G. H. Fu, D. S. Cao, Q. S. Xu, H. D. Li, Y. Z. Liang, Combination of kernel PCA and linear support vector machine for modeling a nonlinear relationship between bioactivity and molecular descriptors. Journal of Chemometrics 2011, 25. 92-99.

33. L. Xu, Q. S. Xu, M. Yang, H. Z. Zhang, C. B. Cai, J. H. Jiang, H. L. Wu, R. Q. Yu, On estimating model complexity and prediction errors in multivariate calibration: generalized resampling by random sample weighting (RSW). Journal of Chemometrics, 2011, 25. 51-58.

34. D. S. Cao, Y. Z. Liang, Q. S. Xu, H. D. Li, X. Chen, A New Strategy of Outlier Detection for QSAR/QSPR. Journal of Computational Chemistry 2010, 31. 592-602.

35. D. S. Cao, Q. S. Xu, Y. Z. Liang, X. A. Chen, H. D. Li, Automatic feature subset selection for decision tree-based ensemble methods in the prediction of bioactivity. Chemometrics and Intelligent Laboratory Systems 2010, 103. 129-136.

36. D. S. Cao, Q. S. Xu, Y. Z. Liang, L. X. Zhang, H. D. Li, The boosting: A new idea of building models. Chemometrics and Intelligent Laboratory Systems 2010, 100. 1-11.

37. H. D. Li, Y. Z. Liang, Q. S. Xu, D. S. Cao, Model population analysis for variable selection. Journal of Chemometrics 2010, 24.418-423.

38. H. D. Li, Y. Z. Liang, Q. S. Xu, Uncover the path from PCR to PLS via elastic component regression. Chemometrics and Intelligent Laboratory Systems 2010, 104. 341-346.

39. B. Haupt, M. R. Schwartz, Q. S. Xu, J. Y. Ro, Columnar cell lesions: a consensus study among pathology trainees. Human Pathology 2010, 41. 895-901.

40. H. D. Li, Y. Z. Liang, Q. S. Xu, Support vector machines and its applications in chemistry. Chemometrics and Intelligent Laboratory Systems 2009, 95. 188-198.

41. H. D. Li, Y. Z. Liang, Q. S. Xu, D. S. Cao, Key wavelengths screening using competitive adaptive reweighted sampling method for multivariate calibration. Analytica Chimica Acta 2009, 648. 77-84.

42. L. Jin, Q. S. Xu, J. Smeyers-Verbeke, D. L. Massart, Updating multivariate calibration with the Delaunay triangulation method: The creation of a new local model. Chemometrics and Intelligent Laboratory Systems 2006, 80. 87-98.

43. Q. S. Xu, F. Daeyaert, P. J. Lewi, D. L. Massart, Studies of relationship between biological activities and HIV reverse transcriptase inhibitors by multivariate adaptive regression splines with curds and whey. Chemometrics and Intelligent Laboratory Systems 2006, 82. 24-30.

44. E. Deconinck, Q. S. Xu, R. Put, D. Coomans, D. L. Massart, Y. V. Heyden, Prediction of gastro-intestinal absorption using multivariate adaptive regression splines. Journal of Pharmaceutical and Biomedical Analysis 2005, 39. 1021-1030.

45. Q. N. Hu, Y. Z. Liang, Q. S. Xu, K. T. Fang, X. L. Peng, H. Yin, Structural features hidden in the degree distributions of topological graphs. Journal of Mathematical Chemistry 2005, 37. 37-56.

46. Y. B. Ji, Q. S. Xu, Y. Z. Hu, Y. V. Heyden, Development, optimization and validation of a fingerprint of Ginkgo biloba extracts by high-performance liquid chromatography. Journal of Chromatography A 2005, 1066. 97-104.

47. L. Jin, Q. S. Xu, D. L. Massart, Multivariate calibration with the Delaunay triangulation method: Definition of the calibration domain. Spectroscopy Letters 2005, 38. 787-807.

48. Q. S. Xu, Y. Z. Liang, Z. T. Hou, A multi-sequential number-theoretic optimization algorithm using clustering methods. Journal of Central South University of Technology 2005, 12. 283-293.

49. M. H. Zhang, Q. S. Xu, F. Daeyaert, P. J. Lewi, D. L. Massart, Application of boosting to classification problems in chemometrics. Analytica Chimica Acta 2005, 544. 167-176.

50. M. H. Zhang, Q. S. Xu, D. L. Massart, Boosting partial least squares. Analytical Chemistry 2005, 77. 1423-1431.

51. R. Put, Q. S. Xu, D. L. Massart, Y. V. Heyden, Multivariate adaptive regression splines (MARS) in chromatographic quantitative structure-retention relationship studies. Journal of Chromatography A 2004, 1055. 11-19.

52. Q. S. Xu, M. Daszykowski, B. Walczak, F. Daeyaert, M. R. de Jonge, J. Heeres, L. M. H. Koymans, P. J. Lewi, H. M. Vinkers, P. A. Janssen, D. L. Massart, Multivariate adaptive regression splines - studies of HIV reverse transcriptase inhibitors. Chemometrics and Intelligent Laboratory Systems 2004, 72. 27-34.

53. Q. S. Xu, S. de Jong, P. Lewi, D. L. Massart, Partial least squares regression with Curds and Whey. Chemometrics and Intelligent Laboratory Systems 2004, 71. 21-31.

54. Q. S. Xu, Y. Z. Liang, Y. P. Du, Monte Carlo cross-validation for selecting a model and estimating the prediction error in multivariate calibration. Journal of Chemometrics 2004, 18. 112-120.

55. M. H. Zhang, J. Luypaert, J. A. F. Pierna, Q. S. Xu, D. L. Massart, Determination of total antioxidant capacity in green tea by near-infrared spectroscopy and multivariate calibration. Talanta 2004, 62. 25-35.

56. M. H. Zhang, Q. S. Xu, D. L. Massart, Averaged and weighted average partial least squares. Analytica Chimica Acta 2004, 504. 279-289.

57. Q. S. Xu, D. L. Massart, Y. Z. Liang, K. T. Fang, Two-step multivariate adaptive regression splines for modeling a quantitative relationship between gas chromatography retention indices and molecular descriptors. Journal of Chromatography A 2003, 998. 155-167.

58. M. H. Zhang, Q. S. Xu, D. L. Massart, Robust principal components regression based on principal sensitivity vectors. Chemometrics and Intelligent Laboratory Systems 2003, 67. 175-185.

59. F. Gan, Q. S. Xu, Y. Z. Liang, Two novel procedures for automatic resolution of two-way data from coupled chromatography. Analyst 2001, 126. 161-168.

60. F. Gong, Y. Z. Liang, Q. S. Xu, F. T. Chau, Gas chromatography-mass spectrometry and chemometric resolution applied to the determination of essential oils in Cortex Cinnamomi. Journal of Chromatography A 2001, 905. 193-205.

61. Q. S. Xu, Y. Z. Liang, Monte Carlo cross validation. Chemometrics and Intelligent Laboratory Systems 2001, 56. 1-11.

62. Y. Z. Liang, K. T. Fang, Q. S. Xu, Uniform design and its applications in chemistry and chemical engineering. Chemometrics and Intelligent Laboratory Systems, 2001, 58. 43-57.

63. Q. S. Xu, Y. Z. Liang, H. L. Shen, Generalized PLS regression. Journal of Chemometrics 2001, 15. 135-148.

64. Q. S. Xu, Y. Z. Liang, K. T. Fang, The effects of different experimental designs on parameter estimation in the kinetics of a reversible chemical reaction. Chemometrics and Intelligent Laboratory Systems 2000, 52. 155-166.

65. Q. S. Xu, Y. Z. Liang, On the equivalence of window factor analysis and orthogonal projection resolution. Chemometrics and Intelligent Laboratory Systems, 1999, 45. 335-338.

66. Yizeng Liang, Qing-song Xu, Hong-dong Li, Dong-sheng Cao, Support Vector Machine and Their Application in Chemistry and Biotechnology, CRC Press, Taylor & Francic Group,2010.8

67. “Identifying Bioactive Components in Natural Products Through Variable Screening”, XIV Chemometrics in Analytical Chemistry, Richmond, Virginia, USA. June 2014

68. “Identifying Bioactive Signature in Natural Products through Chromatographic Fingerprint”. Ninth Winter Symposium on Chemometrics. Tomsk, Russia, Feb. 2014.

69. “Curds and Whey in Calibration with Multiple Responses”, International Conference on Chemometrics and Bioinformatics in Asia, Shanghai, Oct. 2004.

70. “Canonical Partial Least Squares Regression With Multivariate Responses”, PLS’03-- 3rd International Symposium on PLS and Related Methods, Lisbon, Sep. 2003.

71. "QSAR/QSPR Based on Multivariate Adaptive Regression Splines (MARS)" ChemoAC meeting, Brussels, Belgium, Nov.2002.

奖励/荣誉
2009获湖南省自然科学二等奖