DNA computation

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Abstract

This is the first ever doctoral thesis in the field of DNA computation. The field has its roots
in the late 1950s, when the Nobel laureate Richard Feynman first introduced the concept of
computing at a molecular level. Feynman's visionary idea was only realised in 1994, when
Leonard Adleman performed the first ever truly molecular-level computation using DNA
combined with the tools and techniques of molecular biology. Since Adleman reported the
results of his seminal experiment, there has been a flurry
of interest in the idea of using DNA
to perform computations. The potential benefits of using this particular molecule are enormous:
by harnessing the massive inherent parallelism of performing concurrent operations
on trillions of strands, we may one day be able to compress the power of today's supercomputer
into a single test tube. However, if we compare the development of DNA-based
computers to that of their silicon counterparts, it is clear that molecular computers are still
in their infancy. Current work in this area is concerned mainly with abstract models of
computation and simple proof-of-principle experiments. The goal of this thesis is to present
our contribution to the field, placing it in the context of the existing body of work. Our
new results concern a general model of DNA computation, an error-resistant implementation
of the model, experimental investigation of the implementation and an assessment of
the complexity and viability of DNA computations. We begin by recounting the historical
background to the search for the structure of DNA. By providing a detailed description of
this molecule and the operations we may perform on it, we lay down the foundations for subsequent
chapters. We then describe the basic models of DNA computation that have been
proposed to date. In particular, we describe our parallel filtering model, which is the first
to provide a general framework for the elegant expression of algorithms for NP-complete
problems. The implementation of such abstract models is crucial to their success. Previous
experiments that have been carried out suffer from their reliance on various error-prone laboratory
techniques. We show for the first time how one particular operation, hybridisation
extraction, may be replaced by an error-resistant enzymatic separation technique. We also
describe a novel solution read-out procedure that utilizes cloning, and is sufficiently general
to allow it to be used in any experimental implementation. The results of preliminary
tests
of these techniques are then reported. Several important conclusions are to be drawn from these investigations, and we report these in the hope that they will provide useful experimental
guidance in the future. The final contribution of this thesis is a rigorous consideration
of the complexity and viability of DNA computations. We argue that existing analyses of
models of DNA computation are flawed and unrealistic. In order to obtain more realistic
measures of the time and space complexity of DNA computations we describe a new strong
model, and reassess previously described algorithms within it. We review the search for
"killer applications": applications of DNA computing that will establish the superiority
of
this paradigm within a certain domain. We conclude the thesis with a description of several
open problems in the field of DNA computation.

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