Abstract: There is abundant data in the world relevant to any given biological problem, but discovering connections across sources is often laborious and manual. The NCATS Biomedical Data Translator initiative aims to create an openly-available large-scale integration of biomedical and clinical data sources. The Translator integrates multiple types of existing data across the translational spectrum, including objective signs and symptoms of disease, drug effects and intervening types of biological data relevant to understanding pathophysiology to develop new mechanistic nosologies. Here we present our efforts to drive the Translator’s functionality and evaluation using Fanconi anemia, specifically analysis of fundamental biology of Fanconi anemia and generally how rare diseases provide mechanistic understanding of common disease.
Learning Objective 1: The importance of data integration for disease discovery.
Learning Objective 2 (Optional): Rare diseases can inform common disease mechanisms and help identify drug targets.
Melissa Haendel (Presenter)
Oregon Health & Sciences University
Christopher Mungall, Lawrence Berkeley National Laboratory
Julie McMurry, Oregon Health & Sciences University
Christopher Chute, Johns Hopkins University
Maureen Hoatlin, Oregon Health & Science University