DNA self-assembly for efficient error-tolerant nanomanufacturing

• Online Access: http://hdl.handle.net/2047/d20000018

Biology makes things far smaller and more complex than anything produced by human engineering. The biotechnology revolution has for the first time given us the tools necessary to consider engineering on the molecular level. Research in DNA computation, launched by Len Adleman, has opened the door for experimental study of programmable biochemical reactions. In this thesis we focus on a single biochemical mechanism, the self-assembly of DNA structures, that is theoretically sufficient for Turing-universal computation. Wang tiles theory shows how jigsaw-shaped tiles can simulate the operation of a Turing machine. The theory combines Wangs purely mathematical Tiling Problem with the branched DNA constructions of Seeman. DNA molecular structures and intermolecular interactions are particularly amenable to design and are sufficient for the creation of complex molecular objects. Even though DNA self-assembly has potentially many advantages over more traditional manufacturing mechanisms, many challenges are still left unsolved; in particular, process robustness is of a major concern, i.e. robustness refers to the tolerance of errors that may occur in the DNA self-assembly process. As the number of tiles required for the self-assembly of molecular ICs is expected to be in magnitudes of at least millions, even a modest reduction in the error rate has a significant impact on manufacturing. Several works have been reported on error tolerance; proofreading tile sets, snaked proofreading, self-healing tile sets, and so on have proposed new techniques for self-assembly robustness. All these methods have some impacts on the speed of the growth process and by increasing the speed there is no guarantee for an error-free assembly. In this thesis, gross damage in DNA self-assembly has been analyzed and based on the theoretical results a new healing method has been proposed. This healing technique is based on removing the locked faulty tiles from the assembly and regrowing the removed area. Simulation result using xgrow have been reported considering well known tile sets like Line1, Line2, Binarycounter, Sierpinski, and so on. several metrics have been defined for assessing the robustness of a tile set and it has been proved that Ideal Tile Sets (ITS) are the most robust tile sets. Using a Markov model for a tile attachment to an empty site, it has been shown which type of gross damage is more effective for non-ITS tile sets. Then parallel growth (multi-direction/multi-seed) is proposed as a new scheme for increasing the growth process in DNA self-assembly and finally a coding frame work has been proposed for error detection/location in DNA self-assembly and the effectiveness of this coding scheme has been shown for sierpinski tile set.