Modeling structure-function relationships in synthetic DNA sequences using attribute grammars

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dc.contributorVirginia Techen
dc.contributor.authorCai, Yizhien
dc.contributor.authorLux, Matthew W.en
dc.contributor.authorAdam, Lauraen
dc.contributor.authorPeccoud, Jeanen
dc.date.accessed2014-04-30en
dc.date.accessioned2014-06-17T20:12:08Zen
dc.date.available2014-06-17T20:12:08Zen
dc.date.issued2012-04-12en
dc.description.abstractRecognizing 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.en
dc.description.sponsorshipMWL and YC were funded by fellowships from the Virginia Tech Genetics, Bioinformatics, and Computational Biology graduate program. The work was funded by the Virginia Bioinformatics Institute and by the National Science Foundation under grant EF-0850100. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.en
dc.identifier.citationCai Y, Lux MW, Adam L, Peccoud J (2009) Modeling Structure-Function Relationships in Synthetic DNA Sequences using Attribute Grammars. PLoS Comput Biol 5(10): e1000529. doi:10.1371/journal.pcbi.1000529en
dc.identifier.doihttps://doi.org/10.1371/journal.pcbi.1000529en
dc.identifier.issn1553-7358en
dc.identifier.urihttp://hdl.handle.net/10919/49000en
dc.identifier.urlhttp://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1000529en
dc.language.isoen_USen
dc.publisherPublic Library of Scienceen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectDNA sequencesen
dc.subjectGene expressionen
dc.subjectGene regulatory networksen
dc.subjectPhenotypesen
dc.subjectProgramming language semanticsen
dc.subjectSemanticsen
dc.subjectSyntaxen
dc.subjectSynthetic biologyen
dc.titleModeling structure-function relationships in synthetic DNA sequences using attribute grammarsen
dc.title.serialPLoS Computational Biologyen
dc.typeArticle - Refereeden

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