Phoenix, Arizona




Junwen Wang, Ph.D., develops bioinformatics tools, databases and algorithms that allow scientists to annotate genetic variants by analyzing biomedical big data 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 clinical phenotypes, and unravel underlying molecular mechanisms to ultimately benefit patients. Dr. Wang's strategy is to develop more-reliable computational tools for prediction, followed by experimental validation.

Focus areas

  • 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 multi-omics 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 processing, analysis and integration of NGS data — including single cell RNA-seq, ATAC-seq and TCR-seq — for individualized medicine. He is also developing deep learning algorithms to predict enhancer and functional elements in the genome as well as discover 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 and conditions such as lung cancer, cardiovascular disease, back pain and substance misuse to detect disease-specific genes and pathways to better understand disease etiology and develop more-effective therapeutic treatments.

Professional highlights

  • Associate editor, Human Heredity, 2021-present
  • Academic editor, PLOS One, 2013-present
  • Supervisor of recipients of the Award for Outstanding Research Postgraduate Student, University of Hong Kong, 2013-2015
  • Top 1% cited researcher, Thomson Reuters Essential Science Indicators, 2013-2014
  • Recipient, Outstanding Young Researcher Award, University of Hong Kong, 2011-2012


Administrative Appointment

  1. Senior Associate Consultant II-Research, Division of Computational Biology, Department of Quantitative Health Sciences
  2. Senior Associate Consultant II-Research, Division of Molecular Pharmacology and Experimental Therapeutics, Department of Biochemistry and Molecular Biology

Academic Rank

  1. Professor of Biomedical Informatics


  1. MS - Computer Information Technology University of Pennsylvania
  2. Ph.D. - Fisheries/Food Engineering University of Washington
  3. ME - Food Engineering Jiangnan University
  4. BE - Food Engineering Huazhong Agricultural University

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