The Power of Surface-Based DNA Computation

A new model of DNA computation that is based on surface chemistry is studied. Such computations involve the manipulation of DNA strands that are immobilized on a surface, rather than in solution as in the work of Adleman. Surface-based chemistry has been a critical technology in many recent advances in biochemistry and ooers several advantages over solution-based chemistry, including simpliied handling of samples and elimination of loss of strands, which reduce error in the computation. The main contribution of this paper is in showing that surface-based DNA chemistry eeciently supports general circuit computation on many inputs in parallel. To do this, an abstract model of computation that allows parallel manipulation of binary inputs is described. It is then shown that this model can be implemented using fairly standard chemistry, in which inputs are encoded as DNA strands and the strands are repeatedly modiied in parallel on a surface using the chemical processes of hybridization, exonuclease degradation, polymerase extension or ligation. Thirdly, it is shown that the model supports eecient circuit simulation in the following sense: exactly those inputs that satisfy a circuit can be isolated, and the number of parallel operations needed to do this is proportional to the size of the circuit. Finally, results are presented on the power of the model when another resource of DNA computation is limited, namely strand length.