WAN, Xiang

Associate Professor (Adjunct)

Education Background

Ph.D. Computing Science, University of Alberta, 2006

M.S. Computing Science, University of Alberta, 2001

B.S. Information System, Renmin University, 1994

Research Field
Meta-analysis, Data Mining, Large-scale Genomic Data Analysis, High Performance Computing, Evidence-based Medicine
Email
wanxiang@cuhk.edu.cn
Biography

Professor Xiang Wan is an associate professor at The Chinese University of Hong Kong, Shenzhen. Professor Wan received his BA in Information System from Renmin University and his MA and Ph.D. in Computing Science from University of Alberta. Professor Wan was a research assistant professor at Hong Kong Baptist University from 2012 to 2018. And he is now working concurrently as a research scientist at Shenzhen Research Institute of Big Data since 2018.

Professor Wan has been mainly working on meta-analysis and statistical learning, particularly in the field of large-scale genomic data analysis. He has published more than 40 papers in many top-tier journals, including Nature Genetics, American Journal of Human Genetics, BMC Genetics, Bioinformatics, BMC Bioinformatics, Neuro-informatics and IEEE/ACM Transactions on Computational Biology and Bioinformatics, etc. Professor Wan is currently the director of Medical Big Data Lab. The main research goal of this lab is to integrate electronic medical records, medical imaging, health check reports and multi-omics data to help the pre-diagnosis and the personalized treatment.

Academic Publications

1. Can Yang, Xiang Wan*, Xinyi Lin, Mengjie Chen, Xiang Zhou, Jin Liu. CoMM: a collaborative mixed model to dissecting genetic contributions to complex traits by leveraging regulatory information, Bioinformatics 35(10) 1644-1652, 2019. (co-first author)

2. Jingsi Ming, Mingwei Dai, Mingxuan Cai, Xiang Wan, Jin Liu, Can Yang. LSMM: a statistical approach to integrating functional annotations with genome-wide association studies. Bioinformatics, 2019, 34 (16), 2788-2796.

3. Mingwei Dai, Xiang Wan, Heng Peng, Yao Wang, Yue Liu, Jin Liu, Zongben Xu, Can Yang. Joint analysis of individual-level and summary-level GWAS data by leveraging pleiotropy. Bioinformatics, 2019, Bioinformatics 35 (10), 1729-1736.

4. Lili Yue, Gaorong Li, Heng Lian, Xiang Wan. Regression adjustment for treatment effect with multicollinearity in high dimensions. Computational Statistics & Data Analysis, 2019, 134:17-35.

5. Guanying Wu, Xiang Wan*, Baohua Xu. A new estimation of protein-level false discovery rate. BMC Genomics, 2018, 2018 Aug 13;19 (Suppl 6):567. doi: 10.1186/s12864-018-4923-3. (co-first author)

6. Dehui Luo, Xiang Wan*, Jiming Liu, Tiejun Tong,Optimally estimating the sample mean from the sample size, median, mid-range, and/or mid-quartile range,Statistical methods in medical research, 2018, 27 (6), 1785-1805. (co-correspondence author)

7. Yan Zhou, Xiang Wan*, Baoxue Zhang, Tiejun Tong, Classifying next-generation sequencing data using a zero-inflated Poisson model, Bioinformatics,2018, 15;34(8):1329-1335. (co-correspondence author)

8. Jin Liu, Xiang Wan*, Chaolong Wang, Chao Yang, Xiaowen Zhou, Can Yang, LLR: A latent low-rank approach to colocalizing genetic risk variants in multiple GWAS,Bioinformatics, 2017, 33(24):3878-3886. (co-first author)

9. Mingwei Dai, Jingsi Ming, Mingxuan Cai, Jin Liu, Can Yang, Xiang Wan*, ZongbenXue, IGESS: A Statistical Approach to Integrating Individual-Level Genotype Data and Summary Statistics in Genome-Wide Association Studies, Bioinformatics,2017,33(18): 2882-2889. (co-correspondence author)

10. Bin Zhang, Xiang Wan*, Yuhao Dong, Dehui Luo, Jing Liu, Long Liang, Wenbo Chen, Xiaoning Luo, Xiaokai Mo, Lu Zhang, Wenhui Huang, Shufang Pei, Fusheng Ouyang, Baoliang Guo, Changhong Liang, Zhouyang Lian, Shuixing Zhang, Machine Learning Algorithms for Risk Prediction of Severe Hand-Foot-Mouth Disease in Children, Scientific Report, 2017 Jul 14;7(1):5368. (co-first author)

11. Yan Zhou, Baoxue Zhou, Tiejun Tong, Xiang Wan*. GD-RDA: A New Regularized Discriminant Analysis for High-Dimensional Data, Journal of Computational Biology, 2017,24 (11), 1099-1111. (correspondence author)

12. Kai Dong, Hongyu Zhao, Tiejun Tong, Xiang Wan*. NBLDA: Negative Binomial Linear Discriminant Analysis for RNA-Seq Data,BMC Bioinformatics,2016, 17(1):369. (co-correspondence author)

13. Ruixing Ming, Jiming Liu, William K.W. Cheung, Xiang Wan*. Stochastic Modeling of Infectious Diseases for Heterogeneous Populations. BMC Infectious Disease, 2016,5(1):107. (correspondence author)

14. Jin Liu, Xiang Wan, Shuangge Ma, Can Yang. EPS: An empirical Bayes approach to integrating pleiotropy and tissue-specific information for prioritizing risk genes, Bioinformatics, 2016, 32(12):1856-64

15. Ben Teng, Can Yang, Jiming Liu, Zhipeng Cai, Xiang Wan*. Exploring the genetic patterns of complex diseases via the integrative genome-wide approach. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2015, 13(3): 557-664. (correspondence author)

16. Xiang Wan, Wenqian Wang, Jiming Liu, Tiejun Tong. Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range. BMC medical research methodology, 14 (1), 135, 2014.

17. Xiang Wan, Jiming Liu, William Cheung, Tiejun Tong. Learning to improve medical decision making from imbalanced data without a priori cost. BMC medical informatics and decision making, 14 (1), 1, 2014.

18. Xiang Wan, Jiming Liu, William Cheung, Tiejun Tong. Inferring Epidemic Network Topology from Surveillance Data. Plos ONE, 9(6):e100661, 2014.

19. Xiaowei Zhou, Jiming Liu, Xiang Wan*, Weichuan Yu. Piecewise-constant and low-rank approximation for identification of recurrent copy number variations. Bioinformatics, 30(14):1943-1949, 2014. (correspondence author)

20. Xiaowei Zhou, Can Yang, Xiang Wan, Hongyu Zhao, Weichuan Yu. Multisample aCGH Data Analysis via Total Variation and Spectral Regularization. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 10(1): 230-235, 2013.

21. Xiang Wan, Can Yang, Qiang Yang, Hongyu Zhao, Weichuan Yu. HapBoost: A Fast Approach to Boosting Haplotype Association Analyses in Genome-Wide Association Studies. IEEE/ACM Transactions on Computational Biology and Bioinformatics, (1): 207-212, 2013.

22. Xiang Wan, Can Yang, Qiang Yang, Hongyu Zhao, Weichuan Yu. The complete compositional epistasis detection in genome-wide association studies, BMC Genetics, 14(1):7, 2013.

23. Xiang Wan, Can Yang, Qiang Yang, Hongyu Zhao, Weichuan Yu. HapBoost: A Fast Approach to Boosting Haplotype Association Analyses in Genome-Wide Association Studies, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 10(1): 207-212, 2013.

24. Xiaowei Zhou, Can Yang, Xiang Wan, Hongyu Zhao, Weichuan Yu. Multisample aCGH Data Analysis via Total Variation and Spectral Regularization, IEEE/ACM Transactions on Computational Biology and Bioinformatics , 10(1), 207-212, 2013.

25. Xiang Wan, Can Yang, Weichuan Yu. Comments on 'An empirical comparison of several recent epistatic interaction detection methods', Bioinformatics, 28(1):145-146, 2012.

26. Geng Cui, Man Leung Wong, Xiang Wan. Cost-Sensitive Learning via Priority Sampling to Improve the Return on Marketing and CRM. Journal of Management Information System, 29(1):341-374, 2012.

27. Can Yang*, Xiang Wan*, Qiang Yang, Hong Xue, Weichuan Yu. A new two-locus disease association pattern identified in genome-wide association studies, BMC Bioinformatics, 12:156, 2011. (co-first author)

28. Can Yang*, Xiang Wan*, Qiang Yang, Hong Xue, Weichuan Yu. The choice of null distributions for detecting gene-gene interactions in genome-wide association studies, BMC Bioinformatics, 12(Suppl 1):S26, 2011. (co-first author)

29. Lingxing Yung, Can Yang, Xiang Wan, Weichuan Yu. GBOOST: A GPU-Based Tool for Detecting Gene-Gene Interactions in Genome-Wide Case Control Studies, Bioinformatics, 28(1):145-146, 2011

30. Xiang Wan, Can Yang, Qiang Yang, Hong Xue, Xiaodan Fan, Nelson L.S. Tang, Weichuan Yu. BOOST: A fast approach to detecting gene-gene interactions in genome-wide case-control studies, American Journal of Human Genetics, 87(3), 325-340, 2010.

31. Xiang Wan, Can Yang, Qiang Yang, Hong Xue, Nelson L.S. Tang, Weichuan Yu. Detecting two-locus associations allowing for interactions in genome-wide association studies, Bioinformatics, 26(20): 2517-2525, 2010.

32. Xiang Wan, Can Yang, Qiang Yang, Hong Xue, Nelson L.S. Tang, Weichuan Yu. Predictive rule inference for epistatic interaction detection in genome-wide association study, Bioinformatics, 26(1):30-37, 2010.

33. Can Yang, Xiang Wan, Qiang Yang, Hong Xue, Weichuan Yu. Identifying main effects and epistatic interactions from large-scale SNP data via adaptive group lasso, BMC Bioinformatics, 11(Suppl 1):S18, 2010.

34. Xiang Wan, Can Yang, Qiang Yang, Hong Xue, Nelson L.S. Tang, Weichuan Yu. MegaSNPHunter: a learning approach to detect disease predisposition SNPs and high level interactions in genome-wide association study, BMC Bioinformatics, 10:13, 2009.

35. Kimberly L Stark, Bin Xu, Anindya Bagchi, Wen-Sung Lai, Hui Liu, Ruby Hsu, Xiang Wan, Paul Pavlidis, Alea A Mills, Maria Karayiorgou1 & Joseph A Gogos Altered brain microRNA biogenesis contributes to phenotypic deficits in a 22q11-deletion mouse model, Nature Genetics, 40, 751 – 760, 2008.

36. Can Yang, Zengyou He, Xiang Wan, Weichuan Yu, Qiang Yang, Hong Xue, SNPHarvester: a filtering-based approach for detecting epistatic interactions in genome-wide association studies, Bioinformatics, doi:10.1093, 2008.

37. Xiang Wan, Paul Pavlidis. Sharing and reusing gene expression profiling data in neuroscience, Neuroinformatics, 5(3), 161-175, 2007.

38. Xiang Wan, Guohui Lin. CISA: Combined NMR Resonance Connectivity Information Determination and Sequential Assignment, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 4(3), 336-348, 2007.

39. Xiang Wan, Guohui Lin. A Graph-Based Automated NMR Backbone Resonance Sequential Assignment, Journal of Bioinformatics and Computational Biology, 5(2), 313-333, 2007.

40. Guohui Lin, Xiang Wan, Theodos Tegos, Yingshu Li. Statistical Evaluation of NMR Backbone Resonance Assignment, International Journal of Bioinformatics Research and Applications, 2(2), 147-160, 2006.

41. Xiang Wan, Theodos Tegos, Guohui Lin. Histogram-based Scoring Schemes for Protein NMR Resonance Assignment, Journal of Bioinformatics and Computational Biology, 2.