Manuscript Topics

Graphical invariants play a fundamental role in graph theory by providing quantitative and qualitative measures that capture many structural properties of graphs. With the increasing importance of graph-based models in disciplines such as chemistry, physics, biology, computer science, and network science, graphical invariants have become indispensable for understanding complex systems. In chemical graph theory, real-valued graphical invariants are often referred to as topological indices, which are widely used to predict the physicochemical properties of chemical compounds. In network analysis, graphical invariants help quantify robustness, efficiency, centrality, and vulnerability in complex networks. In the biological sciences, these invariants provide a powerful mathematical framework for modeling, analyzing, and interpreting complex biological systems.
This special issue invites contributions that advance the mathematical foundations of graphical invariants, explore their interrelationships, or demonstrate their effectiveness across different application domains. The following is a non-exhaustive list of topics of interest:
• Spectra of graph matrices
• Graph polynomials
• Graph energies
• Graph entropies
• Topological indices
• Centrality-related measures
• Applications of graphical invariants

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