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The Wnt-activated β-catenin and Ca 2+ ions play a critical role in the regulation of physiology of cardiomyocytes. The dysregulation of both the components causes the replacement of myocardial mass right ventricle with fibrous and adipose tissue which results in the condition of Arrhythmogenic Right ventricular Cardiomyopathy (ARVC). The major hurdle in ARVC treatment is lack of effective therapies targeting the underlying root molecular biomarkers of pathogenesis. Despite major advancements in interpreting the mechanism of ARVC etiology, the dynamics of molecular links in underlying biological machinery are still being delineated. Previously, formal methods based computational modeling techniques including kinetic logic, Petri Nets, hybrid automata and static analysis have greatly contributed in increasing our comprehension to decipher the molecular systems dynamics. It has allowed the identification of biomarkers which can be utilized for target-based therapies owing to meticulous biological abstractions along with implementing reference map that confines together the discrete biological insights. In this study, we have performed the static analysis of the Biological Regulatory Networks (BRNs) of the Wnt/β-catenin and Wnt/Ca 2+ signaling pathways to identify the significant biomarkers for ARVC. The abstracted qualitative models of afore mentioned BRNs are first constructed in GINsim software tool and then these models are converted into Automata Network (ANs) Models using Pint software tool. The fix point analysis is performed which contributed in pinpointing the possible therapeutic strategies for ARVC treatment by identification of drug targets such as Gsk3, Ck1 and Axin in Wnt/β-catenin AN and Bak & Bax, Parp, mCalpain, JNk and CIn in Wnt/Ca 2+ AN. Moreover, the Bcl2 gene is identified as novel therapeutic remedy in both the ANs of ARVC. The Bcl2 gene prevents the cardiac apoptosis via positive regulation of Wnt in Wnt/β-catenin AN and through inhibition of Bak & Bax (apoptotic component) in Wnt/Ca 2+ AN.The current study tends to fulfill the scientific gap between wet lab studies and provides cost effective and time saving computational strategies for an effectual treatment for deadly diseases like ARVC.