Location

Rochester, Minnesota

Contact

Wang.Liguo@mayo.edu

SUMMARY

Most diseases can be attributed at least in part to genetic mutations or epigenetic modifications. Current high-throughput sequencing approaches could produce massive data from clinical samples in a cost-effective manner to characterize patients' genomic and epigenomic landscapes. These data are valuable resources for researchers to identify disease-causing variants and facilitate personalized medicine.

The research of Liguo Wang, Ph.D., concentrates on the major theme of developing computational tools and methods to transform these immense data into biological knowledge and provide cognitive supports for data-informed clinical decision-making.

Focus areas

  • Cancer biomarker discovery. Somatic mutation, copy number variation, epigenetic alteration and aberrant RNA splicing are common in human cancers. Dr. Wang's research focuses on identifying new and recurrent cancer biomarkers that are associated with tumor presence (diagnostic), progression and metastasis (prognostic), and drug-resistance (predictive).
  • High-throughput sequencing data analysis, mining and integration. The amount of genomic data is growing exponentially and is spread over numerous heterogeneous data repositories. Dr. Wang's research focuses on developing bioinformatics solutions to analyze, integrate and interpret different types of molecular data including, whole-genome sequencing, whole-exome sequencing, transcriptome sequencing, bisulfite sequencing, ChIP sequencing and other types of epigenomic data.
  • Prostate cancer development and progression. The androgen receptor (AR) plays critical roles in prostate cancer development, progression and metastasis. Dr. Wang's research focuses on using genome-wide approaches to study how the AR interacts with cis-regulatory DNA elements, trans-regulatory protein factors as well as the epigenetic environments during prostate cancer development and progression.

Significance to patient care

Big data promises precise medicine. Data-informed clinical decision-making demands storing, retrieving, analyzing and integrating a large amount of molecular and clinical data.

Professional highlights

  • Associate editor, BMC Bioinformatics, 2014-present

PUBLICATIONS

See my publications

PROFESSIONAL DETAILS

Administrative Appointment

  1. Senior Associate Consultant II-Research, Department of Health Sciences Research
  2. Senior Associate Consultant II-Research, Department of Biochemistry and Molecular Biology

Academic Rank

  1. Associate Professor of Biomedical Informatics

EDUCATION

  1. Postdoctoral Research Fellowship - Biostatistics and Informatics Dan L. Duncan Cancer Center, Baylor College of Medicine
  2. Ph.D. - Computational Biology Beijing Genomics Institute, Chinese Academy of Sciences
  3. BS - Bioscience Xuzhou Normal University, School of Biosciences
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BIO-00055202

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