scholarly journals ShortBOL: A Language for Scripting Designs for Engineered Biological Systems Using Synthetic Biology Open Language (SBOL)

2020 ◽  
Vol 9 (4) ◽  
pp. 962-966 ◽  
Author(s):  
Matthew Crowther ◽  
Lewis Grozinger ◽  
Matthew Pocock ◽  
Christopher P. D. Taylor ◽  
James A. McLaughlin ◽  
...  
Keyword(s):  
Synthetic Biology ◽  
Biological Systems ◽  
Synthetic Biology Open Language

scholarly journals Capturing Multicellular System Designs Using the Synthetic Biology Open Language (SBOL)

2018 ◽  
Author(s):  
Bradley Brown ◽  
Christian Atallah ◽  
James Alastair McLaughlin ◽  
Göksel Misirli ◽  
Ángel Goñi-Moreno ◽  
...  
Keyword(s):  
Synthetic Biology ◽  
Biological Systems ◽  
Data Standard ◽  
Homogeneous Systems ◽  
System Behaviour ◽  
Synthetic Biology Open Language ◽  
And Function ◽  
Multiple Cells ◽  
System Designs ◽  
Multicellular System

AbstractSynthetic biology aims to improve the development of biological systems and in-crease their reproducibility through the use of engineering principles, such as stan-dardisation and modularisation. It is important that these systems can be represented and shared in a standard way to ensure they are easily understood, reproduced, and utilised by other researchers. The Synthetic Biology Open Language (SBOL) is a data standard for sharing biological designs and information about their implementation and characterisation. Thus far, this standard has been used to represent designs in homogeneous systems, where the same design is implemented in every cell. In recent years there has been increasing interest in multicellular systems, where biological designs are split across multiple cells to optimise the system behaviour and function. Here we show how the SBOL standard can be used to represent such multicellular systems, and hence how researchers can better share designs with the community.

scholarly journals A standard-enabled workflow for synthetic biology

2017 ◽  
Vol 45 (3) ◽  
pp. 793-803 ◽  
Author(s):  
Chris J. Myers ◽  
Jacob Beal ◽  
Thomas E. Gorochowski ◽  
Hiroyuki Kuwahara ◽  
Curtis Madsen ◽  
...  
Keyword(s):  
Systems Biology ◽  
Synthetic Biology ◽  
Markup Language ◽  
Design Tools ◽  
Data Standards ◽  
Data Repositories ◽  
Simulation Tools ◽  
Systems Biology Markup Language ◽  
Visualization Tools ◽  
Synthetic Biology Open Language

A synthetic biology workflow is composed of data repositories that provide information about genetic parts, sequence-level design tools to compose these parts into circuits, visualization tools to depict these designs, genetic design tools to select parts to create systems, and modeling and simulation tools to evaluate alternative design choices. Data standards enable the ready exchange of information within such a workflow, allowing repositories and tools to be connected from a diversity of sources. The present paper describes one such workflow that utilizes, among others, the Synthetic Biology Open Language (SBOL) to describe genetic designs, the Systems Biology Markup Language to model these designs, and SBOL Visual to visualize these designs. We describe how a standard-enabled workflow can be used to produce types of design information, including multiple repositories and software tools exchanging information using a variety of data standards. Recently, the ACS Synthetic Biology journal has recommended the use of SBOL in their publications.

A Validator and Converter for the Synthetic Biology Open Language

2017 ◽  
Vol 6 (7) ◽  
pp. 1161-1168 ◽  
Author(s):  
Zach Zundel ◽  
Meher Samineni ◽  
Zhen Zhang ◽  
Chris J. Myers
Keyword(s):  
Synthetic Biology ◽  
Synthetic Biology Open Language

scholarly journals SBOL Visual 2 Ontology

2020 ◽  
Author(s):  
Göksel Misirli ◽  
Jacob Beal ◽  
Thomas E. Gorochowski ◽  
Guy-Bart Stan ◽  
Anil Wipat ◽  
...  
Keyword(s):  
Synthetic Biology ◽  
Web Service ◽  
Visual Representation ◽  
Biological Ontologies ◽  
Visualization Tools ◽  
Synthetic Biology Open Language

AbstractStandardising the visual representation of genetic parts and circuits is vital for unambiguously creating and interpreting genetic designs. To this end, an increasing number of tools are adopting well-defined glyphs from the Synthetic Biology Open Language (SBOL) Visual standard to represent various genetic parts and their relationships. However, the implementation and maintenance of the relationships between biological elements or concepts and their associated glyphs has to now been left up to tool developers. We address this need with the SBOL Visual 2 Ontology, a machine-accessible resource that provides rules for mapping from genetic parts, molecules, and interactions between them, to agreed SBOL Visual glyphs. This resource, together with a web service, can be used as a library to simplify the development of visualization tools, as a stand-alone resource to computationally search for suitable glyphs, and to help facilitate integration with existing biological ontologies and standards in synthetic biology.Graphical TOC Entry

scholarly journals Independent control of amplitude and period in a synthetic oscillator circuit with modified repressilator

2022 ◽  
Vol 5 (1) ◽  
Author(s):  
Fengyu Zhang ◽  
Yanhong Sun ◽  
Yihao Zhang ◽  
Wenting Shen ◽  
Shujing Wang ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Synthetic Biology ◽  
Biological Systems ◽  
Reporter Genes ◽  
Quantitative Model ◽  
Theoretical Level ◽  
Independent Control ◽  
Oscillator Circuit ◽  
Biological Circuits

AbstractSynthetic Biology aims to create predictable biological circuits and fully operational biological systems. Although there are methods to create more stable oscillators, such as repressilators, independently controlling the oscillation of reporter genes in terms of their amplitude and period is only on theoretical level. Here, we introduce a new oscillator circuit that can be independently controlled by two inducers in Escherichia coli. Some control components, including σECF11 and NahR, were added to the circuit. By systematically tuning the concentration of the inducers, salicylate and IPTG, the amplitude and period can be modulated independently. Furthermore, we constructed a quantitative model to forecast the regulation results. Under the guidance of the model, the expected oscillation can be regulated by choosing the proper concentration combinations of inducers. In summary, our work achieved independent control of the oscillator circuit, which allows the oscillator to be modularized and used in more complex circuit designs.

scholarly journals Synthetic Biology Open Language Visual (SBOL Visual) Version 2.1

2019 ◽  
Vol 16 (2) ◽  
Author(s):  
Curtis Madsen ◽  
Angel Goni Moreno ◽  
Zachary Palchick ◽  
Umesh P ◽  
Nicholas Roehner ◽  
...  
Keyword(s):  
Nucleic Acid ◽  
Synthetic Biology ◽  
Molecular Species ◽  
Chemical Process ◽  
Structure And Function ◽  
Genomic Context ◽  
Functional Relationships ◽  
Synthetic Biology Open Language ◽  
And Function ◽  
Biological Organisms

AbstractPeople who are engineering biological organisms often find it useful to communicate in diagrams, both about the structure of the nucleic acid sequences that they are engineering and about the functional relationships between sequence features and other molecular species . Some typical practices and conventions have begun to emerge for such diagrams. The Synthetic Biology Open Language Visual (SBOL Visual) has been developed as a standard for organizing and systematizing such conventions in order to produce a coherent language for expressing the structure and function of genetic designs. This document details version 2.1 of SBOL Visual, which builds on the prior SBOL Visual 2.0 standard by expanding diagram syntax to include methods for showing modular structure and mappings between elements of a system, interactions arrows that can split or join (with the glyph at the split or join indicating either superposition or a chemical process), and adding new glyphs for indicating genomic context (e.g., integration into a plasmid or genome) and for stop codons.

Integrating the whole from the sum of the parts: vignettes in computational biology

2017 ◽  
Vol 1 (3) ◽  
pp. 241-243
Author(s):  
Jeffrey Skolnick
Keyword(s):  
Deep Learning ◽  
Drug Discovery ◽  
Synthetic Biology ◽  
Personalized Medicine ◽  
Computational Biology ◽  
Biological Systems ◽  
Deep Understanding ◽  
Biological Processes ◽  
Practical Applications ◽  
Biological Variables

As is typical of contemporary cutting-edge interdisciplinary fields, computational biology touches and impacts many disciplines ranging from fundamental studies in the areas of genomics, proteomics transcriptomics, lipidomics to practical applications such as personalized medicine, drug discovery, and synthetic biology. This editorial examines the multifaceted role computational biology plays. Using the tools of deep learning, it can make powerful predictions of many biological variables, which may not provide a deep understanding of what factors contribute to the phenomena. Alternatively, it can provide the how and the why of biological processes. Most importantly, it can help guide and interpret what experiments and biological systems to study.

Specifying Combinatorial Designs with the Synthetic Biology Open Language (SBOL)

2019 ◽  
Vol 8 (7) ◽  
pp. 1519-1523
Author(s):  
Nicholas Roehner ◽  
Bryan Bartley ◽  
Jacob Beal ◽  
James McLaughlin ◽  
Matthew Pocock ◽  
...  
Keyword(s):  
Synthetic Biology ◽  
Combinatorial Designs ◽  
Synthetic Biology Open Language

scholarly journals Are the biomedical sciences ready for synthetic biology?

2020 ◽  
Vol 11 (1) ◽  
pp. 23-31
Author(s):  
Maxwell S. DeNies ◽  
Allen P. Liu ◽  
Santiago Schnell
Keyword(s):  
Synthetic Biology ◽  
Biomedical Research ◽  
Molecular Level ◽  
Biological Systems ◽  
Science Research ◽  
Functional System ◽  
Biomedical Sciences ◽  
Present Evidence ◽  
Experimental Control ◽  
Discovery Science

AbstractThe ability to construct a functional system from its individual components is foundational to understanding how it works. Synthetic biology is a broad field that draws from principles of engineering and computer science to create new biological systems or parts with novel function. While this has drawn well-deserved acclaim within the biotechnology community, application of synthetic biology methodologies to study biological systems has potential to fundamentally change how biomedical research is conducted by providing researchers with improved experimental control. While the concepts behind synthetic biology are not new, we present evidence supporting why the current research environment is conducive for integration of synthetic biology approaches within biomedical research. In this perspective we explore the idea of synthetic biology as a discovery science research tool and provide examples of both top-down and bottom-up approaches that have already been used to answer important physiology questions at both the organismal and molecular level.

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