BackgroundThe generation of Big Data has enabled systems‐level dissections into the mechanisms of cardiovascular pathology. Integration of dozens of variables across a variety of platforms and across laboratories fosters discoveries through multidisciplinary investigations, decreased costs, and elimination of unnecessary redundancy in research efforts. Moreover, Big Data brings speed, allowing more rapid and improved decision making. The Mouse Heart Attack Research Tool (mHART) harnesses a large dataset of over 10 years of experiments from a single site, for use by investigators to generate novel hypotheses, uncover hidden relationships, and identify new predictive markers of progressive cardiac remodeling following myocardial infarction (MI) in mice.Methods and ResultsWe designed the mHART database to incorporate our own data, with future plans to integrate community participation. We generated genomic, proteomic, physiological, biochemical, and cellular outputs from plasma and left ventricles obtained from post‐MI and no MI (naïve) control groups. We included both male and female mice ranging in age from 3 to 36 months old. After variable collection, data underwent quality assessment to clean the data (i.e. to eliminate technical errors), check for completeness, remove duplicates, and define terms. Combined, mHART 1.0 contains >888,000 data points and includes results from >2,000 unique mice. Database performance was tested and an example applied to illustrate how this database can be used.ConclusionThe efforts reported here establish the first version of the mHART database.Support or Funding InformationThis abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.