Computing with biological macromolecules, such as DNA, is fundamentally a physical/chemical process. The DNA chemistry introduces a level of complexity that makes reliable, e cient, and scalable computations a challenge. All the chemical and thermodynamic factors have to be analyzed and controlled in order for the molecular algorithm to produce the intended result. For instance, a computation based on DNA requires that the problem instance be encoded in single strands of DNA and that these strands react as planned, that molecular biology protocols, such as PCR or a nity separation, correctly extract the result, and that su cient exibility remains so that worthwhile computations can be done. In this paper, various thermodynamic and chemical constraints on DNA computing are enumerated. A similarity measure, based on Gibb's free energy of formation, is de ned to judge the goodness of DNA encodings. Finally, the DNA computation problem for implementing molecular algorithms is de ned, and it is likely that it is as di cult as the combinatorial optimization problems they are intended to solve. 1

Abstract. The design of DNA sequences is a key problem for implementing molecular self-assembly with nucleic acid molecules. These molecules must meet several physical, chemical and logical requirements, mainly to avoid mishybridization. Since manual selection of proper sequences is too time-consuming for more than a handful of molecules, the aid of computer programs is advisable. In this paper two software tools for designing DNA sequences are presented, the DNASequenceGenerator and the DNASequence-Compiler. Both employ an approach of sequence dissimilarity based on the uniqueness of overlapping subsequences and a graph based algorithm for sequence generation. Other sequence properties like melting temperature or forbidden subsequences are also regarded, but not secondary structure errors or equilibrium chemistry. Fields of application are DNA computing and DNA-based nanotechnology. In the second part of this paper, sequences generated with the DNASequenceGenerator are compared to those from several publications of other groups, an example application for the DNASequenceCompiler is presented, and the advantages and disadvantages of the presented approach are discussed. 1

The importance of DNA sequence design for reliable DNA computing is well recognized. In this paper, we describe a DNA sequence optimization system NACST/Seq that is based on a multiobjective genetic algorithm. It uses the concept of Pareto optimization to reflect many realistic characteristics of DNA sequences in real bio-chemical experiments flexibly. This feature allows to recommend multiple candidate sets as well as to generate the DNA sequences, which fit better to a specific DNA computing algorithm. We also describe DNA sequence analyzer that can examine and visualize the properties of given DNA sequences.

Abstract—Molecular computing has proved its possibility to solve weighted graph problem such as Hamiltonian Path Problem (HPP), Traveling Salesman Problem (TSP)