Title :
An Improved Invariant for Matching Molecular Graphs Based on VF2 Algorithm
Author :
Huiliang Shang ; Yudong Tao ; Yuan Gao ; Chen Zhang ; Xiaoling Wang
Author_Institution :
Electron. Eng. Dept., Fudan Univ., Shanghai, China
Abstract :
The molecular graph is a specific kind of graph. The classical method to solve the molecular graph matching problem is VF2 algorithm, where a heuristic is utilized to reduce the search space by analyzing the substructure of matched nodes. However, this heuristic invariant performs badly due to the strong similarity among some molecular graphs, thus the traditional VF2 algorithm has high time complexity. This paper introduces a novel heuristic invariant to effectively improve the computational efficiency, generated by the optimized circuit simulation method. We also conduct a series of experiments on PubChem dataset. The performance of the proposed algorithm is given by compared with the classical one.
Keywords :
bioinformatics; chemistry computing; computational complexity; graph theory; search problems; PubChem dataset; VF2 algorithm; computational efficiency; heuristic invariant; molecular graph matching problem; optimized circuit simulation method; search space; time complexity; Admittance; Circuit simulation; Cybernetics; Equations; Heuristic algorithms; Integrated circuit modeling; Time complexity; Circuit simulation method; VF2 algorithm; molecular graph matching;
Journal_Title :
Systems, Man, and Cybernetics: Systems, IEEE Transactions on
DOI :
10.1109/TSMC.2014.2327058