The JSB lab is led by the PI, Dr. Jingyi Jessica Li, with around ten highly motivated graduate and undergraduate students. Our research is at the junction of statistics and biology, as our lab name JSB represents. We focus on developing statistical and computational methods motivated by important questions in biomedical sciences and abundant information in big genomic and health related data. On the statistical methodology side, our example interests include association measures, high-dimensional variable selection, and classification metrics. On the biomedical application side, our example interests include next-generation RNA sequencing, comparative genomics, and information flow in the central dogma. 

If you are interested in our research, please check out our YouTube channel.

56. Ge, X.*, Chen, Y.E.*, Song, D., McDermott, M., Woyshner, K., Manousopoulou, A., Wang, N., Li, W., Wang, L.D., and Li, J.J. (2021). Clipper: p-value-free FDR control on high-throughput data from two conditions. Genome Biology 22:288. [ SOFTWARE ] [ CODE ] [ VIDEO ] | [ PDF ]
52. Jiang, R., Li, W.V., and Li, J.J. (2021). mbImpute: an accurate and robust imputation method for microbiome data. Genome Biology 22:192. [ UCLA News ] [ SOFTWARE ] | [ PDF ]