Junwen Wang, Ph.D., develops bioinformatics tools, databases and algorithms to analyze biomedical big data, to annotate genetic variants and to construct gene regulatory networks. Dr. Wang is actively collaborating with biologists and clinicians to apply these methodologies to specific diseases for research and clinical treatments. He is currently focusing his research on lung, breast, brain and colon cancers.
Genome-wide association studies (GWAS), next-generation sequencing (NGS) and other high-throughput platforms are generating large amounts of data. A challenge facing researchers is how to efficiently analyze and interpret data, reduce false-positives, link to clinic phenotypes, and unravel underlying molecular mechanisms to ultimately benefit our patients. Dr. Wang's strategy is to develop more-reliable computational tools for prediction, followed by experimental validation.
- Genetic variants and diseases. Dr. Wang is developing algorithms to efficiently call germline and somatic mutations from NGS data, build databases for genetic variants from GWAS, and develop novel methods to annotate and prioritize these variants — particularly regulatory variants.
- Data integration and network biology. Dr. Wang is interested in integrative analysis of multiomics data for gene regulatory network inference and the detection of cancer driver genes. He is particularly experienced in using publicly available big data to infer functions and interactions of variants, genes and pathways.
- Genomics, deep learning and precision medicine. Dr. Wang is developing bioinformatics pipelines for data process, analyzing and integration of NGS data (including single cell RNA-seq) for individualized medicine. He is also developing deep learning algorithms to predict enhancer and functional elements in the genome, and novel drug targets for cancer treatment. He is actively involved in various projects sponsored by Mayo Clinic's Center for Individualized Medicine.
Significance to patient care
Genetic variants, genes and pathways can be used as biomarkers for individualized treatment and prognosis strategies. The bioinformatics and deep learning methods developed by Dr. Wang are being applied to diseases such as lung, brain and colon cancers, multiple myeloma, cardiovascular disease and substance abuse to detect disease-specific genes and pathways to better understand the disease etiology and develop better therapeutic treatments.
- Associate editor, Human Heredity, 2016-present
- Academic editor, PLoS One, 2013-present
- Supervisor to recipients of the Award for Outstanding Research Postgraduate Student, The University of Hong Kong, 2013-2015
- Top 1% cited researcher, Thomson Reuters Essential Science Indicator, 2013-2014
- Recipient, Outstanding Young Researcher Award, The University of Hong Kong, 2011-2012