The Bioinformatics Shared Resource (BISR) collaborates with clinical, cancer control, and basic science investigators to use genomics and informatics approaches in cancer research.

We help researchers

  • Better understand the complex processes involved in the development and progression of various types of cancer.
  • Use this knowledge to predict cancer recurrence, metastasis and response to therapies.
  • Assign patients to specific targeted therapies, such as immunotherapies, to improve survival and quality-of-life.

Our objectives for improving patient outcomes include

  • Identifying germline and somatic genetic and epigenetic alterations that are associated with the development and progression of cancer.
  • Identifying genetic and epigenetic events and mutation signatures in cancers caused by environmental factors, such as tobacco.
  • Identifying ethnicity-related genetic and epigenetic alterations that may be underlying factors in health disparities.
  • Utilizing genetic and epigenetic information for early detection of cancer (personalized risk prediction) and prediction of cancer recurrence and progression (personalized monitoring).
  • Promoting precision medicine (personalized intervention).
  • Understanding the functional mechanisms by which genetic and epigenetic findings have a direct effect on cancer.

Areas of Focus and Goals

The primary goal of the BISR is to facilitate the peer-reviewed research and extramural grant application of Wake Forest Baptist Comprehensive Cancer Center members. We collaborate with members from all scientific programs throughout all phases of cancer-related research projects.

Major responsibilities are assumed for methodological-, computational-, and bioinformatics-related issues, including study design (such as sample size, platform, sequencing depth, etc.), sampling, interim reviews, and final analysis and result delivery.

We focus on:

  • Bioinformatics-based design and data analysis in support of grant development and publications.
  • Informatics services to Comprehensive Cancer Center investigators from all programs, including genomics data processing, bioinformatics analyses, data annotation and visualization/sharing to support basic, translational and clinical cancer research by leveraging the institutionally maintained Translational Data Warehouse.
  • Leadership, education, and training, including participating in graduate-level courses and T32 training grants.
  • Mentoring teams for K awardees and other young investigators.
  • Facilitating membership and leadership on committees responsible for scientific and administrative decisions for the Comprehensive Cancer Center.
  • Providing short courses on statistical or bioinformatics methods for Comprehensive Cancer Center members.