A DNA-based solution to the graph isomorphism problem using Adleman–Lipton model with stickers

• Published in: Applied mathematics and computation Vol. 197; no. 2; pp. 672 - 686
• Main Authors: Hsieh, Sun-Yuan, Chen, Ming-Yu
• Format: Journal Article
• Language: English
• Published: New York, NY Elsevier Inc 01.04.2008; Elsevier
• Subjects: Biological operations; Data engineering applications on bioinformatics; DNA-based algorithms; DNA-based computing; Exact sciences and technology; Mathematical analysis; Mathematics; Molecular computing; NP-complete; Numerical analysis; Numerical analysis. Scientific computation; Sciences and techniques of general use; The graph isomorphism problem; Data engineering applications on bioinformatics; Molecular computing; The graph isomorphism problem; NP-complete; DNA-based algorithms; DNA-based computing; Biological operations; Polynomial; Combinatorial problem; Optimization method; Combinatorial optimization; Algorithm; Numerical analysis; Applied mathematics; DNA; Isomorphism
• ISSN: 0096-3003; 1873-5649
• DOI: 10.1016/j.amc.2007.08.005

Since the experimental demonstration of its feasibility, DNA-based computing has been applied to a number of decision or combinatorial optimization problems. The graph isomorphism problem belongs to the class of NP problems, and has been conjectured intractable, although probably not NP-complete. In this paper, we demonstrate the power of DNA-based computing by showing the graph isomorphism problem can be efficiently solved under this computation model. By generating the solution space using stickers, we present DNA-based algorithms to solve the problem using polynomial number of basic biological operations.