Dr Xuejun Liu
	Room 228 College of Computer Science & Technology Building A12, 29 Yudao Str. Nanjing University of Aeronautics & Astronautics Nanjing, 210016 Phone: +88 (0)25 84896490-12230 E-mail: xuejun.liu@nuaa.edu.cn

Research Interests

• Microarray data analysis
• Aerodynamic data analysis
• Statistics and probabilistics

Teachings

• Programming language I
• Machining learning
  

Graduate Students

• Zhang, Li
• Gao, Zhenzhu
• Yan, Guoqi
• Zheng, Yaqian
• Jin, Jing
• Li, Meng
• Zhu, Qinglei
• Li, Zhenghao
• Wu, Kuanzhan
• Shi, Xinxin
• Zhang, Wujun
  

Former Students

• Jin, Shenghua
• Shan, Zhihui
• Zhao, Zhilan
• Xu, Yafeng
  

Publications

• Liu, X., Gao, Z., Zhang, L. and Rattray, M., puma 3.0: improved uncertainty propagation methods for gene and transcript expression analysis, BMC Bioinformatics, 2013 14:39. (Journal link )
  
• Yan, G., Liu, X. and Lu, H., Fast airfoil design based on multi-output Gaussian process regression, the 5nd Chinese Society of Aeronautics and Astronautics (CSAA) Science and Technique Youth Forum, 7-10 October 2012, Nanchang, China.(In Chinese)
  
• Zhao, Z., Liu, X. and Zhang, L., A probabilsitic model for the analysis of RNA-Seq data, CBME'2011, 30 Oct - 1 Nov 2011, Wuhan, China. (Third youth paper award, in Chinese)
  
• Gao, Z., Liu, X., Zhang, L. and Rattray, M., A probabilistic model for probe-level analysis of Affymeterix exon arrays, CBME'2011, 30 Oct - 1 Nov 2011, Wuhan, China. (in Chinese)
  
• Xu, Y., Liu, X. and Lu, H., Fast airfoil design based on CST parameterization, Aeronautical Computing Technique, 2011, 41(5): 25-33.(in Chinese)
  
• Liu, X. and Rattray, M., Including probe-level measurement error in robust mixture clustering of replicated microarray gene expression, Statistical Applications in Genetics and Molecular Biology: 2010 Vol. 9 : Iss. 1, Article 42. (Journal link )
  
• Jin, S., Liu, X. and Zhang, L., The application of noise characteristics of primary Affymetrix GeneChip data, Chinese Society of Biomedical Engineering (CSBME) Annual Meeting, 2-4 December 2010, Beijing, China. (Best youth paper award, in Chinese)
  
• Shan, Z., Liu, X. and Lu, H., Gaussian process regression for fast evaluation of airfoil aerodynamic performance, the 4nd Chinese Society of Aeronautics and Astronautics (CSAA) Science and Technique Youth Forum, 25-26 November 2010, Beijing, China.(In Chinese)
  
• Zhang, L. and Liu, X., An improved probabilistic model for finding differential gene expression, the 2nd International Conference on BioMedical Engineering and Informatics, 17-19 October 2009, Tianjin, China.(Download )
  
• Pearson, R., Liu, X., Sanguinetti, G., Milo, M., Lawrence, N. D. and Rattray, M., puma: a Bioconductor package for Propagating Uncertainty in Microarray Analysis, BMC Bioinformatics, 2009 10:211. (featured article, Journal link )
  
• Liu, X., Lin, K. K., Andersen, B. and Rattray, M., Including probe-level uncertainty in model-based gene expression clustering, BMC Bioinformatics, 2007 8:98. (Journal link )
  
• Liu, X., Milo, M., Lawrence, N. D. and Rattray, M., Probe-level measurement error improves accuracy in detecting differential gene expression, Bioinformatics, 2006 22(17): 2107-2113. (Journal link )
  
• Rattray, M., Liu, X., Sanguinetti, G., Milo, M. and Lawrence, N. D., Propagating uncertainty in Microarray data analysis, Briefings in Bioinformatics, 2006 7(1):37-47. (Jounal link)
  
• Liu, X., Milo, M., Lawrence, N. D. and Rattray, M., A tractable probabilistic model for Affymetrix probe-level analysis across multiple chips, Bioinformatics, 2005 21(18):3637-3644. (Jounal link)
  

Software

• pumaclustii: an R package to propagate probe-level measurement error in a robust t-mixture clustering model for replicated gene expression data.

• mmgmos: an R package to estimate the expression levels and the confidence of measures for multiple arrays of the same type of Affymetrix GeneChips using the multi-chip modified gamma Model for Oligonucleotide Signal (multi-mgMOS) and the modified gamma Model for Oligonucleotide Signal (mgMOS).

• pplr: an R package to include probe-level measurement error into the variance estimates of gene expression levels and to detect up-regulated genes by calculating probability of positive log-ratio (PPLR).

• pumaclust: an R package to propagate probe-level measurement error in the model-based clustering of gene expression data.