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Modeling Scalable Pattern Generation in DNA Reaction Networks.

ABSTRACT: We have developed a theoretical framework for developing patterns in multiple dimensions using controllable diffusion and designed reactions implemented in DNA. This includes so-called strand displacement reactions in which one single-stranded DNA hybridizes to a hemi-duplex DNA and displaces another single-stranded DNA, reversibly or irreversibly. These reactions can be designed to proceed with designed rate and molecular specificity. By also controlling diffusion by partial complementarity to a stationary, cross-linked DNA, we can generate predictable patterns. We demonstrate this with several simulations showing deterministic, predictable shapes in space.

SUBMITTER: Allen PB

PROVIDER: S-EPMC4261192 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature

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Modeling Scalable Pattern Generation in DNA Reaction Networks.

Allen Peter B PB Chen Xi X Simpson Zack B ZB Ellington Andrew D AD

Natural computing 20141201 4

We have developed a theoretical framework for developing patterns in multiple dimensions using controllable diffusion and designed reactions implemented in DNA. This includes so-called strand displacement reactions in which one single-stranded DNA hybridizes to a hemi-duplex DNA and displaces another single-stranded DNA, reversibly or irreversibly. These reactions can be designed to proceed with designed rate and molecular specificity. By also controlling diffusion by partial complementarity to ...[more]

PMID: 25506295

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