Dr. Jingyi Jessica Li’s research is at the junction of statistics and biology, as her group name JSB represents. The group focuses 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.
Starting from 2000, Dr. Ker-Chau Li’s research interest turned to the emerging field of computation/mathematics/statistics in genome biology. In 2002, Dr. Li published a paper in Proceedings of Academy of Science, featuring the novel method of liquid association (LA) for microarray gene expression analysis. Dr. Li is currently leading a research group in UCLA and in Academia Sinica to continue the development of methods for utilizing multiple sources of gene expression profiling, genetic markers, complex disease phenotypes and traits. A website http://kiefer.stat2.sinica.edu.tw/LAP3 offers on-line computation based on LA and related methods for gene expression studies. Dr. Li is also collaborating with Dr. Pan Chyr Yang of National Taiwan University and his colleagues on integrative cancer biology.
Dr. Zhou’s group develop statistical methodologies for efficient analysis of large-scale high-throughput genomic data. Dr. Zhou and students employ model-based and sparse regularization methods to make statistical inference on these data. The goal is to understand gene regulation and decode regulatory circuits by integrating gene expression data, protein binding data, chromatin interaction data, and DNA sequence data. The group members have constructed gene regulatory networks and identified combinatorial binding patterns in mouse embryonic stem cells. In addition, the group also has biological applications in alternative splicing and complex diseases via collaborations with experimental groups.