MAY 09, 2018 12:00 PM PDT

Knowledge Portals: Accelerating Action from Genetic Data

C.E. CREDITS: P.A.C.E. CE | Florida CE
  • Director, Operations & Development, Knowledge Portals & Diabetes Research, Broad Institute of MIT and Harvard
      Noël Burtt is the Director of Operations and Development, Knowledge Portals and Diabetes, at the Broad Institute, providing organizational leadership and developing research strategies for the program. She defines and stewards new collaborations/research initiatives, identifies funding opportunities, and performs resource allocation and planning. She also oversees operations and external relations for the Accelerating Medicines Partnership for Type 2 Diabetes (AMP-T2D) Program and leads scientific operations for the AMP-T2D Data Coordinating Center. She is responsible for the continued growth of the T2D Knowledge Portal and that of the emerging Knowledge Portals for additional complex diseases.

      Noël began her career developing technologies for genotyping and sequencing at the Whitehead Center for Genome Research (now the Broad Institute), and transitioned into scientific project management for an array of international genome-wide association studies. Building standardized approaches to data and analysis activities, communication and data sharing, and organizational and operational procedures in order to promote collaboration has been a consistent theme throughout her career.


    The Knowledge Portal Network is a set of interconnected, open-access web resources that aggregate, harmonize, analyze, and present genetic associations and epigenomic annotations for complex diseases, in order to help researchers elucidate the molecular details of disease mechanisms and find new therapeutic targets. It currently includes the Type 2 Diabetes (, Cardiovascular (, and Cerebrovascular ( Knowledge Portals. The Portals present an analytical and computational framework whereby researchers can instantaneously search a comprehensive, up-to-date collection of association results and epigenomic annotations relevant to a particular complex disease, all seamlessly integrated with one another, and perform custom association analyses that query securely protected individual-level data. 

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