Algorithmic Self-Assembly of DNA
File : pdf, 1.9 MB, 109 pages
Thesis by Eric Winfree
TOC
1 Contributions
1.1 Introduction to DNA-Based Computation
1.2 Models of Computation by Self-Assembly
1.3 Experiments with Self-Assembly
1.4 Publication List
1.5 Support
2 Introduction to DNA-Based Computation
2.1 Why Compute with Molecules, and How?
2.2 Computing Inverse Sets with DNA
2.2.1 Abstract Models of Molecular Computation
2.2.2 Branching Programs
2.2.3 Correspondence of Models
2.2.4 Corollaries and Conclusions
2.2.5 Discussion
2.3 0(1) Methods for DNA Computation
2.3.1 Solving FSAT in O(1) biosteps
2.3.2 Combinatorial Sets of GOTO Programs
2.3.3 Single-Strand Computation of Boolean Circuits
2.3.4 Conclusions and Future Directions
3 Models of Computation by Self-Assembly
3.1 2D Self-Assembly for Computation
3.1.1 Some Basic Annealing Reactions
3.1.2 Operations Using Linear DNA
3.1.3 Operations Using Branched DNA
3.1.4 Comparison with Other Approaches
3.2 Graph-Theoretic Models of DNA Self-Assembly
3.2.1 Language Theory and Grammars
3.2.2 DNA Complexes and Self-Assembly Rules
3.2.3 Linear Self-Assembly is Equivalent to Regular Languages
3.2.4 Dendrimer Self-Assembly is Equivalent to Context-Free Languages
3.2.5 Two Dimensional Self-assembly is Universal
3.2.6 Solving the Hamiltonian Path Problem
3.2.7 Three Dimensional Self-Assembly Augments Computational Power
3.2.8 Discussion
3.3 Simulation of Self-Assembly Thermodynamics and Kinetics
3.3.1 An Abstract Model of 2D Self-Assembly
3.3.2 Implementation by Self-Assembly of DNA
3.3.3 A Kinetic Model of DNA Self-Assembly
3.3.4 Simulation Results
3.3.5 Analysis
3.3.6 Discussion
3.3.7 Conclusions
4 Experiments with DNA Self-Assembly
4.1 A Competition Experiment: Slot-Filling
4.1.1 Materials and Methods
4.1.2 Results
4.1.3 Discussion
4.2 Experiments with 2D Lattices
4.2.1 Design of DNA Crystal
4.2.2 Materials and Methods
4.2.3 Results of Characterization by Gel Electrophoresis
4.2.4 Results of AFM Imaging
4.2.5 Control of Surface Topography
4.2.6 Applications
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