Connection number topological aspect for backbone DNA networks

Area of Science:

• Chemical graph theory
• Computational biology
• Network science

Background:

• DNA networks exhibit complex topological characteristics crucial for biological function.
• Understanding network structure aids in analyzing information flow and robustness.
• The Connection Number (CN) is an emerging metric for network analysis.

Purpose of the Study:

• To investigate the topological properties of DNA networks using the Connection Number (CN).
• To compute novel connection-based topological descriptors for DNA networks.
• To elucidate the role of CN in characterizing DNA network structure and dynamics.

Main Methods:

• Utilized rigorous mathematical modeling and analysis.
• Employed direct computation methods for topological descriptors.
• Calculated hyper Zagreb connection index, augmented connection index, and others.

Main Results:

• Established the significance of the Connection Number in DNA network analysis.
• Computed several connection-based topological indices for backbone DNA and its barycentric subdivision networks.
• Demonstrated the utility of these descriptors in understanding network robustness.

Conclusions:

• The Connection Number provides profound insights into DNA network topology and dynamics.
• Connection-based topological descriptors are valuable tools for studying complex biological networks.
• This research contributes to the understanding of DNA network structures through chemical graph theory.