Jin Liu is an Assistant Professor at the Centre for Quantitative Medicine and the Signature Programme in Health Services and Systems Research, Duke-NUS. His research interest is primarily focused on the development of novel statistical methodologies for big data in genetics, which includes large-scale genome-wide association studies and integration of multi-omics analysis.
A/Professor Liu has been involved with several research projects on genetics/genomic studies and currently serves as the Principal Investigator for statistical genetics research at Duke-NUS which provides him experience on organising research teams, communicating with collaborators, solidifying realistic research plans and delivering research results in a timely manner.
Yeung Kar Fu
Dr. Liu’s research interests include the development of novel statistical methodology for the analysis of high dimensional data, which includes microarray analysis; genome-wide association studies (GWAS) and next generation sequencing (NGS). Dr. Liu has developed quite a few statistical methodologies in integrative analysis of multiple cancer studies. He is particularly interested in developing novel penalized regression methods to integrate the multiple-platform data in genomic studies. Dr. Liu also has broad interests over other areas, e.g. statistical computing, mixed models and empirical Bayes. Dr. Liu had been involved with several National Institutes of Health funded research projects on genomic studies and currently serves as the biostatistician for genetics research at Duke-NUS, which provide him some experience on organizing research teams, communicating with collaborators, solidifying realistic research plans, and delivering research results in a timely manner.
Liu J, Wan X, Wang C, Yang C, Zhou X, Yang C. LLR: a latent low-rank approach to colocalizing genetic risk variants in multiple GWAS. Bioinformatics. 2017 Aug 14;33(24):3878-86.
Liu J, Huang J, Zhang Y, Lan Q, Rothman N, Zheng T, Ma S. Integrative analysis of prognosis data on multiple cancer subtypes. Biometrics. 2014 Sep 1;70(3):480-8.
Liu J, Huang J, Ma S, Wang K. Incorporating group correlations in genome-wide association studies using smoothed group Lasso. Biostatistics. 2012 Sep 17;14(2):205-19.