On the scalability of biocomputing algorithms: The case of the maximum clique problem

Abstract

The paper aims at demonstrating and confirming that breadth first search or pruning techniques can substantially improve the effectiveness of biomolecular algorithms. A breadth first search-based DNA algorithm solving the maximum clique problem for a graph is presented, and its complexity and scalability parameters are studied. The analysis shows that parameters like the number of steps, the length and volume of DNA strands, the number of enzymes and the concentration of the molecules encoding solutions are dramatically improved in comparison with previous approaches to the same problem and, theoretically, they would allow to process graphs with thousands of vertices. These parameters are also compared with several related results focusing on the scalability of DNA computing methods. Finally, an analysis of error-resistance of the algorithm is given.