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Dr. Wong is an expert in international interdisciplinary research. She has in-depth knowledge of statistics, computer science, and biology. She has held numerous leadership positions working on algorithms for next-generation sequencing data at Illumina Ltd., in Cambridge, UK, and Inova Translational Medicine Institute. Prior to joining DCEG in 2022, she served as president and chief data scientist of Coherent Logic Limited, where she consulted on data analytics and helped organizations leverage the public cloud for genomics analysis. 

Dr. Wong received her M.S. and Ph.D. in biometry (biological statistics) from Cornell University, where she developed statistical models of the processes of molecular evolution using sequence data. She has a B.S. in genetics, bacteriology, mathematics, computer sciences and statistics from the University of Wisconsin - Madison. 

Research Interests

Big Data Analytics in Bioinformatics 

Dr. Wong is interested in developing reproducible bioinformatics analysis frameworks using cloud and high-performance computing and data technologies, as well as promoting the adoption of the latest technologies. She believes that reproducible bioinformatics pipelines should adhere to interoperability and pluggability design principles and that scientific data management should follow FAIR data principles. She is keen on developing and promoting the usage of Application Programming Interface (API) functions that build on big data analysis frameworks that can be used in Jupyter and R notebooks.  

Germline and Somatic Mutational Processes

Dr. Wong has made important contributions to our understanding of the correlation between parental ages and the mutational processes in germline de novo mutations in the offspring. She is interested in studying the association between germline variants and somatic mutational signatures. She hypothesizes that an integrative mutational model that includes multiple types of variants would improve the identification of new mutational signatures in both germline and somatic mutational processes.  

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