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The <italic>Wnt</italic>-activated <inline-formula> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula>-<italic>catenin</italic> and <inline-formula> <tex-math notation="LaTeX">$Ca^{2+}$ </tex-math></inline-formula> 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 <italic>Wnt/</italic> <inline-formula> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula>-<italic>catenin</italic> and <italic>Wnt/Ca</italic> 2&#x002B; 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 <italic>Gsk3, Ck1 and Axin</italic> in <italic>Wnt/</italic> <inline-formula> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula>-<italic>catenin AN</italic> and <italic>Bak &#x0026; Bax, Parp, mCalpain, JNk and CIn</italic> in <italic>Wnt/Ca</italic> 2&#x002B; AN. Moreover, the <italic>Bcl2</italic> gene is identified as novel therapeutic remedy in both the ANs of ARVC. The <italic>Bcl2</italic> gene prevents the cardiac apoptosis via positive regulation of <italic>Wnt</italic> in <italic>Wnt/</italic> <inline-formula> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula>-<italic>catenin</italic> AN and through inhibition of <italic>Bak &#x0026; Bax</italic> (apoptotic component) in <italic>Wnt/Ca</italic> 2&#x002B; 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.

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A Static Analysis of <italic>Wnt</italic>/<italic>&#x03B2;</italic>-Catenin and <italic>Wnt</italic>/<italic>Ca</italic>2&#x002B; Biological Regulatory Networks for ARVC Using Automata Network Model

A Static Analysis of Wnt/β-Catenin and Wnt/Ca2+ Biological Regulatory Networks for ARVC Using Automata Network Model

A Static Analysis of Wnt/β-Catenin and Wnt/Ca²⁺ Biological Regulatory Networks for ARVC Using Automata Network Model