Representations of different molecular mechanisms help in deciphering the detailed pathophysiology of diseases. They can be examined as either sets or networks of elements. The intersection of two sets is the set of all objects that are members of both the sets. Intersection can be implemented manually as well as using most programming languages. Hypertrophic cardiomyopathy (HCM), which is the most common genetic cardiac disease, has a prevalence of 1 in 500 people. We applied intersection on various levels of HCM representations���element, interaction, and subnetwork level���and found it useful for finding shared pathophysiologic mechanisms, as a difference finder, and as noise removal. At the element level, the intersection was found useful for comparing the representations. It was used on both raw molecular elements and the results of network analysis. At the interaction level, the intersection was used for data refinement and finding the shared pathophysiologic mechanisms of HCM and its clinical courses. At the subnetwork level, the intersection was used for finding common molecular mechanisms as well as comparing representations. Apart from these, the intersection also has the potential to be used for the discovery of biomarkers and drug targets. The use of intersection proved to be a simple and effective for exploring the representations of HCM molecular mechanisms.