Ruibin Xi

Statistical analysis of next-generation sequencing, bioinformatics, cancer genomics, precision on-cology, single cell RNA sequencing, statistical computing, big data analysis, high-dimensinal data analysis, Bayesian statistics.

Statistical analysis of ambient air pollution, macro-economy and human health (2016), Responsible for RMB U430,000 (around US $70,000), National Key Basic Research Program of China, Co-Principal Investigator

Big data driven models and algorithms for management decision (2015), Responsible for RMB U320,000 (around US $50,000), National Natural Science Foundation of China, Co-Principal Investigator

Statistical analyses of genomic variations based on high-throughtput sequencing data (2015), RMB U600,000 (around US $100,000), National Natural Science Foundation of China, Principal Investigator

Statistical Learning of Unstructured Data: Mathematical Foundation and Algorithms (2015), Responsible for RMB U580,000 (around US $100,000), National Key Basic Research Program of China, Co-Principal Investigator

Nonlinear dimension reduction of high dimensional data (2013), RMBU30,000(aroundUS$5,000),Microsoft-PKU Joint Lab Grant, Principal Investigator

Statistical analysis of cancer genomics data (2013), RMB U300,000 (around US $50,000), 985 Project, Peking University, Principal Investigator

Agilent 2011 eMerging Insights Grants (2011), US $75,000, Co-Principal Investigator

1. Xia,Y., Liu, Y., Deng, M. and Xi, R.* (2018+) Detecting virus integration sites based on multiple related sequencing data by VirTect, BMC Medical Genomics,Accepted.

2. Xia, Y., Liu, Y., Deng, M. and Xi, R.* (2017) SVmine improves structural variation detection by integrative mining of predictions from multiple algorithms, Bioinformatics, 1;33(21):3348-3354.

3. Yuan, H. Xi, R.*, Chen, C. and Deng, M.* (2017) Differential network analysis via lasso penalized D-trace loss, Biometrika, 104 (4):755-770.

4. Xia, Y., Liu Y., Deng, M. and Xi, R. * (2017) Pysim-sv: a package for

simulating structural variation data with GC-biases, BCM Bioinformatics,

18(Suppl 3):53.

5. Xi, R.*, Lee, S., Xia, Y., Kim, T. and Park, P.* (2016) Copy number analysis of whole-genome data using BIC-seq2 and its application to detection of cancer susceptibility variants, Nucleic Acids Research, 44(13): 6274-86.

6. Xi, R.*, Li, Y. and Hu, Y. (2015) Bayesian quantile regression based on the empirical likelihood with spike and slab priors, Bayesian Analysis,

11(3):821-855.

7. Xi, R. and Lin, N.* (2015) Direct regression modelling of high-order moments in big data, Statistics and Its Interface, 9(4):445-452.

8. Yang, L., Luquette, L.J., Gehlenborg, N., Xi, R., Haseley, P.S., Hsieh, C.H.,Zhang, C., Ren, X., Protopopov, A., Chin, L., Kucherlapati, R., Lee, C. and Park P.J.* (2013) Diverse mechanisms of somatic structural variations in human cancer genomes, Cell, 153(4):919-929.

9. Xi, R., Lin, N., Chen, Y.* and Kim, Y. (2012) Compression and aggregation of Bayesian estimates for data intensive computing, Knowledge and Information Systems, 33(1):191-212.

10. Xi, R., Hadjipanayis, A.G., Luquette, L.J., Kim, T.M., Lee, E., Zhang, J.H.,Johnson, M.D., Muzny, D.M., Wheeler, D.A., Kucherlapati, R., and Park, P.* (2011) Copy number alteration detection in sequencing data using the Bayesian information criterion, Proceedings of the National Academy of Sciences, USA,108(46):E1128-1136.