Genetic Design Automation Worflows

<p>Comparison between the design automation loop in EDA and GDA. Projects follow parallel paths in both fields. Understanding what lessons from EDA can be applied for GDA is crucial to accelerating discovery in synthetic biology.</p

Parameterization of a Stochastic Model of Gene Expression from Adaptive Imaging Cytometry Data

<p>Supplementary material to a manuscript under review. The manuscript can be downloaded from the link below. </p> <p><strong>Abstract</strong></p> <p>Recent decades have yielded an understanding of cellular behavior as arising from a complicated soup of noisy molecular interactions. Systems biologists use this perspective to build models to explain cellular behavior, while synthetic biologists attempt to forward engineer novel function in this complex environment. It is well known that some cellular behaviors can be explained only when the stochasticity of the underlying molecular dynamics are considered; however, models that capture this molecular noise are exceedingly difficult to construct. First, current datasets typically do not capture time courses of individual cells and rely on fluorescent reporters that do not detail the dynamics of underlying components, such as mRNA. Second, matching stochastic models to single-cell data is far more difficult than matching deterministic models to population averages. In this work, we addressed both of these concerns by using a novel instrument based on time-lapse microscopy and by applying a distribution-based method to assess the match between model and data. We demonstrate our model’s ability to match our experimental data in detail, and then use the model to successfully predict the behavior of a modified system. Our approach should lead to more predictive models of simple genetic systems in both systems and synthetic biology.</p

SBOL: A community standard for communicating designs in synthetic biology

<p>Abstract</p> <p>The Synthetic Biology Open Language (SBOL) is a proposed data standard for exchanging designs within the synthetic biology community. SBOL represents synthetic biology designs in a community-adopted, formalized format for exchange between software tools, research groups, and commercial service providers. The re-use of previously validated designs is critical to the evolution of synthetic biology from a research discipline to an engineering practice. As a community-driven standard, SBOL adapts as synthetic biology evolves, providing specific capabilities for different aspects of the synthetic biology workflow. The SBOL Developers Group has implemented SBOL 1.1 as an XML/RDF serialization and provides software libraries and specification documentation to help developers implement SBOL in their own software. This paper also reports on early successes, including a demonstration of the utility of SBOL for information exchange between three different tools from three academic sites.</p> <p> </p