Browsing by Author "Adam, Laura"

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    Mapping Genotype to Phenotype using Attribute Grammar
    Adam, Laura (Virginia Tech, 2013-09-20)
    Over the past 10 years, several synthetic biology research groups have proposed tools and domain-specific languages to help with the design of artificial DNA molecules. Community standards for exchanging data between these tools, such as the Synthetic Biology Open Language (SBOL), have been developed. It is increasingly important to be able to perform in silico simulation before the time and cost consuming wet lab realization of the constructs, which, as technology advances, also become in themselves more complex. By extending the concept of describing genetic expression as a language, we propose to model relations between genotype and phenotype using formal language theory. We use attribute grammars (AGs) to extract context-dependent information from genetic constructs and compile them into mathematical models, possibly giving clues about their phenotypes. They may be used as a backbone for biological Domain-Specific Languages (DSLs) and we developed a methodology to design these AG based DSLs. We gave examples of languages in the field of synthetic biology to model genetic regulatory networks with Ordinary Differential Equations (ODEs) based on various rate laws or with discrete boolean network models. We implemented a demonstration of these concepts in GenoCAD, a Computer Assisted Design (CAD) software for synthetic biology. GenoCAD guides users from design to simulation. Users can either design constructs with the attribute grammars provided or define their own project-specific languages. Outputting the mathematical model of a genetic construct is performed by DNA compilation based on the attribute grammar specified; the design of new languages by users necessitated the generation on-the-fly of such attribute grammar based DNA compilers. We also considered the impact of our research and its potential dual-use issues. Indeed, after the design exploration is performed in silico, the next logical step is to synthesize the designed construct's DNA molecule to build the construct in vivo. We implemented an algorithm to identify sequences of concern of any length that are specific to Select Agents and Toxins, helping to ensure safer use of our methods.
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    Modeling structure-function relationships in synthetic DNA sequences using attribute grammars
    Cai, Yizhi; Lux, Matthew W.; Adam, Laura; Peccoud, Jean (Public Library of Science, 2012-04-12)
    Recognizing that certain biological functions can be associated with specific DNA sequences has led various fields of biology to adopt the notion of the genetic part. This concept provides a finer level of granularity than the traditional notion of the gene. However, a method of formally relating how a set of parts relates to a function has not yet emerged. Synthetic biology both demands such a formalism and provides an ideal setting for testing hypotheses about relationships between DNA sequences and phenotypes beyond the gene-centric methods used in genetics. Attribute grammars are used in computer science to translate the text of a program source code into the computational operations it represents. By associating attributes with parts, modifying the value of these attributes using rules that describe the structure of DNA sequences, and using a multi-pass compilation process, it is possible to translate DNA sequences into molecular interaction network models. These capabilities are illustrated by simple example grammars expressing how gene expression rates are dependent upon single or multiple parts. The translation process is validated by systematically generating, translating, and simulating the phenotype of all the sequences in the design space generated by a small library of genetic parts. Attribute grammars represent a flexible framework connecting parts with models of biological function. They will be instrumental for building mathematical models of libraries of genetic constructs synthesized to characterize the function of genetic parts. This formalism is also expected to provide a solid foundation for the development of computer assisted design applications for synthetic biology.