Difference between revisions of "DNA Sticky End Design and Assignment for Robust Algorithmic Self-assembly"
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|abstract=Theories of the logic and kinetics of algorithmic self-assembly make many idealizations that eliminate complexities and clarify essential insights. But those complexities are still there when one tries to create self-assembling systems in the laboratory. Which ones are most important, what effects do they have, and how can one design molecules and systems to minimize assembly errors? Examining these questions from both biophysical and combinatorial angles lead us to a DNA sequence design algorithm that may perform orders of magnitude better than previous methods. | |abstract=Theories of the logic and kinetics of algorithmic self-assembly make many idealizations that eliminate complexities and clarify essential insights. But those complexities are still there when one tries to create self-assembling systems in the laboratory. Which ones are most important, what effects do they have, and how can one design molecules and systems to minimize assembly errors? Examining these questions from both biophysical and combinatorial angles lead us to a DNA sequence design algorithm that may perform orders of magnitude better than previous methods. | ||
|authors=Constantine G. Evans and Erik Winfree | |authors=Constantine G. Evans and Erik Winfree | ||
| − | |file=http://www.dna.caltech.edu/Papers/StickyDesign2013.pdf | + | |file=[http://www.dna.caltech.edu/Papers/StickyDesign2013.pdf DNA Sticky End Design and Assignment for Robust Algorithmic Self-assembly] |
}} | }} | ||
Revision as of 12:27, 22 June 2021
Published on: 2013/09/09
Abstract
Theories of the logic and kinetics of algorithmic self-assembly make many idealizations that eliminate complexities and clarify essential insights. But those complexities are still there when one tries to create self-assembling systems in the laboratory. Which ones are most important, what effects do they have, and how can one design molecules and systems to minimize assembly errors? Examining these questions from both biophysical and combinatorial angles lead us to a DNA sequence design algorithm that may perform orders of magnitude better than previous methods.
Authors
Constantine G. Evans and Erik Winfree
File
DNA Sticky End Design and Assignment for Robust Algorithmic Self-assembly
