A Methodology to Annotate Systems Biology Markup Language Models with the Synthetic Biology Open Language

Roehner, Nicholas; Myers, Chris J.

doi:10.1021/sb400066m

Cited by 29 publications

(36 citation statements)

References 29 publications

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“…First, computational tools have to be developed to aid the design process. These programs need to be able to simulate the dynamics of a circuit and convert the designs into a linear assembly of genetic parts 68,202–205 . Insulating DNA sequences will be critical in future circuits because the majority of parts will be in new contexts 206,207 .…”

Section: Discussionmentioning

confidence: 99%

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Principles of genetic circuit design

2014

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Cells are able to navigate environments, communicate, and build complex patterns by initiating gene expression in response to specific signals. Engineers need to harness this capability to program cells to perform tasks or build chemicals and materials that match the complexity seen in nature. This review describes new tools that aid the construction of genetic circuits. We show how circuit dynamics can be influenced by the choice of regulators and changed with expression “tuning knobs.” We collate the failure modes encountered when assembling circuits, quantify their impact on performance, and review mitigation efforts. Finally, we discuss the constraints that arise from operating within a living cell. Collectively, better tools, well-characterized parts, and a comprehensive understanding of how to compose circuits are leading to a breakthrough in the ability to program living cells for advanced applications, from living therapeutics to the atomic manufacturing of functional materials.

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Section: Discussionmentioning

confidence: 99%

“…Model equations and parameters are included in the SI in SMBL format 205,227 . Parameters were adjusted to demonstrate the effect of each tuning knob on circuit behavior.…”

Section: Figurementioning

confidence: 99%

Principles of genetic circuit design

2014

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“…In particular, Cello exports an SBOL file for the AND gate that is imported and compiled by iBioSim into an SBML model (Roehner and Myers 2014). This model is then extended and simulated as described above (see sections Data Analysis and Simulation and Example).…”

Section: Data Exchange and Standardizationmentioning

confidence: 99%

Design Automation in Synthetic Biology

Appleton

Madsen

Roehner

et al. 2017

Cold Spring Harb Perspect Biol

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Design automation refers to a category of software tools for designing systems that work together in a workflow for designing, building, testing, and analyzing systems with a target behavior. In synthetic biology, these tools are called bio-design automation (BDA) tools. In this review, we discuss the BDA tools areas-specify, design, build, test, and learn-and introduce the existing software tools designed to solve problems in these areas. We then detail the functionality of some of these tools and show how they can be used together to create the desired behavior of two types of modern synthetic genetic regulatory networks.S ynthetic biology as a discipline has concerned itself with "forward engineering" living systems. This is a purposefully grand goal and is faced with numerous scientific, engineering, political, and ethical challenges. These engineering challenges include the storage of biological information, the design of complex, interacting biological systems using that information, the physical creation of these systems, and the dissemination of foundational principles as abstractions on which the next technical advances can be made. What should be clear to even the most casual observer is that computers, and the computational capabilities they bring with them, are going to be required if the field is going to succeed going forward. Debates remain regarding the framing of the computational approaches (Andrianantoandro et al. 2006;Lux et al. 2012;Densmore and Bhatia 2014), but there are few who debate the important and increasingly prominent role of computation in the field.Synthetic biology and its associated promise have attracted a wide variety of participants. In particular, computer engineers and computer scientists began developing computational tools for engineering these genetic systems using techniques from their disciplines. Electronic design automation (EDA) showed a clear process by which design formalisms could be built, software tools created, and a larger, separate industry developed (see latticeautomation.com; teselagen.com; deskgen.com; benchling.com). This pursuit in the synthetic biology field has recently been coined bio-design automation (BDA) (Densmore 2012). BDA often uses a "divide and conquer" approach for solving small parts of a larger problem one piece at a time and allows for specialists to tackle specific narrow problems in which they have considerable ex-

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“…The most concerted effort is the Synthetic Biology Open Language (SBOL) consortia, a group of life scientists, engineers, computer scientists and mathematicians that are actively building a set of standards that define a common data format for bioparts and their accompanying characterization data (Bower et al, 2010; Galdzicki et al, 2011; Quinn et al, 2013; Roehner and Myers, 2013). The concept is to create a file structure that can capture biopart sequence, characterization and experimental data in a format that is platform independent.…”

Section: Designing Predictable Biologymentioning

confidence: 99%

Developments in the Tools and Methodologies of Synthetic Biology

Kelwick

MacDonald

Webb

et al. 2014

Front. Bioeng. Biotechnol.

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Synthetic biology is principally concerned with the rational design and engineering of biologically based parts, devices, or systems. However, biological systems are generally complex and unpredictable, and are therefore, intrinsically difficult to engineer. In order to address these fundamental challenges, synthetic biology is aiming to unify a “body of knowledge” from several foundational scientific fields, within the context of a set of engineering principles. This shift in perspective is enabling synthetic biologists to address complexity, such that robust biological systems can be designed, assembled, and tested as part of a biological design cycle. The design cycle takes a forward-design approach in which a biological system is specified, modeled, analyzed, assembled, and its functionality tested. At each stage of the design cycle, an expanding repertoire of tools is being developed. In this review, we highlight several of these tools in terms of their applications and benefits to the synthetic biology community.

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A Methodology to Annotate Systems Biology Markup Language Models with the Synthetic Biology Open Language

Cited by 29 publications

References 29 publications

Principles of genetic circuit design

Principles of genetic circuit design

Design Automation in Synthetic Biology

Developments in the Tools and Methodologies of Synthetic Biology

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