Background

Having completed the Post-Secondary Advanced Level Education in Science (Biology Group) at the New Method College in Hong Kong, Dr. Leo Wang-Kit Cheung moved to Canada to continue his education. Dr. Cheung received his B.Sc. in Mathematics (courses also fulfilled the requirements for the Statistics Major) from the University of Winnipeg with the University Silver Medal in Science and the University Gold Medal in Statistics. He received his M.Sc. in Statistics from the University of Manitoba, and was awarded the University of Manitoba Graduate Fellowship for his Ph.D. studies. With his intense interests in the interface among Statistics, Computer Science, Genetics, and Molecular Biology, he worked on novel probabilistic, statistical and computational approaches for pattern recognition in genomes for his Ph.D. dissertation. Dr. Cheung received his Ph.D. in Statistics (Ph.D. Thesis: Statistical Pattern Recognition in Genomic DNA Sequences) from the University of Manitoba, and moved to the Cancer Research Center of Hawaii (CRCH) at the University of Hawaii to start his faculty position as an Assistant Professor in Biostatistics and Bioinformatics. He has been working as a consultant specializing in Bioinformatics and Computational Biology since 1995. In 2004 Dr. Cheung established the Informatics Shared Resource (ISR) at the CRCH, served as the Director of ISR (ISR was one of the newest Informatics/Bioinformatics Core facilities funded by the National Cancer Institute), and also started his adjunct appointment as an Assistant Professor in the Department of Information and Computer Sciences at the University of Hawaii, Manoa. In 2006 Dr. Cheung moved to the Loyola University Medical Center (LUMC) of Loyola University Chicago to lead a Bioinformatics Program.

Research

Dr. Cheung’s research has been focusing on the development and application of mathematical, statistical, and computational pattern recognition methods for recognition of gene promoters and for analysis of different aspects of gene expression profiles. He has been developing his own research program in Bioinformatics and Computational Biology for Cancer Genomics and Proteomics. His major research interests consist of three research streams. The first research stream is concerned with simple and compound pattern/motif recognition and data mining in “omics” to help understand more about gene expression, gene-gene and gene-environment interactions at different levels. Specific research includes mathematical & statistical investigations of multiple sequence patterns/motifs or molecular signatures/meta-signatures and their joint distributions in genomes, transcriptomes and proteomes, statistical analysis of regulatory sequences (e.g. promoters, enhancers, etc.) controlling the expression of genes, statistical & computational knowledge discovery on alternative splicing mechanism, gene network inference from the analysis of DNA microarray data, and biopathway modeling & simulation. Dr. Cheung received a SUN Microsystems Academic Equipment Grant for Bioinformatics on “Statistical and Computational Approaches to Genomics and Proteomics” and CRCH developmental funds on “Statistical Pattern Recognition Methods for Profiling Gene Expression Patterns”. He has been also a co-principal investigator on a Department of Defense funded Nutrigenomics project with Dr. Loic Le Marchand at CRCH on “Nutrition and Cancer: A Study on the Effects of Cancer-Preventive Foods on Genome-Wide Gene Expression”. The second research stream is concerned with genetic epidemiology and genetic mapping through linkage analysis and association studies. Specific research includes Bayesian statistical methods and machine-learning techniques for whole genome association studies based on haplotype-tagging single nucleotide polymorphisms (ht-SNPs) data, mapping quantitative trait loci (QTL) and dissecting complex polygenic architectures of quantitative traits. The third research stream is concerned with mathematical & statistical biophysical studies on spatial structures, geometry and dynamics of interacting biomolecules. Specific research includes probabilistic modeling and molecular dynamics simulations of DNA, RNA (especially micro-RNA) and proteins. Facing the challenges in these individually exciting research topics, Dr. Cheung is currently working on a novel multidimensional class of probabilistic models that can be used as a new analytical tool to incorporate multiple sources of different kinds of data to help understand and investigate various aspects of human health and the development of many complex diseases in an integrated fashion. The application focus of this work is on studying biological processes and biochemical pathways related to programmed cell death or apoptosis and the development of various tumors and cancers.

Teaching and Services

Dr. Cheung has taught various courses in Statistics and Biostatistics since 1996. In 2004 Dr. Cheung teamed with faculty in Information and Computer Sciences of the University of Hawaii to offer a new graduate course in Bioinformatics, and was selected to serve on the University of Hawaii Bioinformatics Advisory Board. He helped develop the bioinformatics component of the new University of Hawaii Center for Genomics, Proteomics, and Bioinformatics Research Initiative. With support from the Maui High Performance Computing Center, an Air Force Research Laboratory Center managed by the University of Hawaii, he has been utilizing the supercomputer facility to further his research in Bioinformatics. Dr. Cheung also served as a developer of the Vocabularies and Common Data Elements (VCDE) Workspace, one of the Cross Cutting Workspaces, of the NCI Cancer Biomedical Informatics Grid (caBIG) project ( http://cabig.nci.nih.gov). He and Dr. Lynne Wilkens at CRCH headed an effort to make the NCI thesaurus more functional in terms of nutritional vocabularies used in Cancer Epidemiology. Furthermore, he was a VCDE Mentor/Facilitator of the Microarray Repositories Special Interest Group and the Informatics for Proteomics Special Interest Group of the Integrative Cancer Research Workspace, one of the Domain Workspaces of the NCI caBIG. As a Biostatistician and Bioinformatician at the Loyola University Medical Center (LUMC), Dr. Cheung works collaboratively with other researchers of the Center providing biostatistical and bioinformatics consultation and support to joint research projects. He has established a Bioinformatics Core, has been serving as the Bioinformatics Core Director and functioning as a key Bioinformatician at LUMC.