scholarly journals Synthetic Biology Open Language (SBOL) Version 2.0.0

2015 ◽  
Vol 12 (2) ◽  
pp. 902-991 ◽  
Author(s):  
Bryan Bartley ◽  
Jacob Beal ◽  
Kevin Clancy ◽  
Goksel Misirli ◽  
Nicholas Roehner ◽  
...  
Keyword(s):  
Metabolic Engineering ◽  
Synthetic Biology ◽  
Molecular Biology ◽  
Best Practices ◽  
Data Model ◽  
Biological Design ◽  
Exchange Of Information ◽  
Functional Aspects ◽  
Version 2.0 ◽  
Synthetic Biology Open Language

Summary Synthetic biology builds upon the techniques and successes of genetics, molecular biology, and metabolic engineering by applying engineering principles to the design of biological systems. The field still faces substantial challenges, including long development times, high rates of failure, and poor reproducibility. One method to ameliorate these problems would be to improve the exchange of information about designed systems between laboratories. The Synthetic Biology Open Language (SBOL) has been developed as a standard to support the specification and exchange of biological design information in synthetic biology, filling a need not satisfied by other pre-existing standards. This document details version 2.0 of SBOL, introducing a standardized format for the electronic exchange of information on the structural and functional aspects of biological designs. The standard has been designed to support the explicit and unambiguous description of biological designs by means of a well defined data model. The standard also includes rules and best practices on how to use this data model and populate it with relevant design details. The publication of this specification is intended to make these capabilities more widely accessible to potential developers and users in the synthetic biology community and beyond.

scholarly journals Synthetic Biology Open Language (SBOL) Version 2.1.0

2016 ◽  
Vol 13 (3) ◽  
Author(s):  
Jacob Beal ◽  
Robert Sidney Cox ◽  
Raik Grünberg ◽  
James McLaughlin ◽  
Tramy Nguyen ◽  
...  
Keyword(s):  
Metabolic Engineering ◽  
Synthetic Biology ◽  
Molecular Biology ◽  
Best Practices ◽  
Basic Sequence ◽  
Special Issue ◽  
Biological Design ◽  
Version 2.0 ◽  
Topology Information ◽  
Synthetic Biology Open Language

SummarySynthetic biology builds upon the techniques and successes of genetics, molecular biology, and metabolic engineering by applying engineering principles to the design of biological systems. The field still faces substantial challenges, including long development times, high rates of failure, and poor reproducibility. One method to ameliorate these problems would be to improve the exchange of information about designed systems between laboratories. The Synthetic Biology Open Language (SBOL) has been developed as a standard to support the specification and exchange of biological design information in synthetic biology, filling a need not satisfied by other pre-existing standards. This document details version 2.1 of SBOL that builds upon version 2.0 published in last year’s JIB special issue. In particular, SBOL 2.1 includes improved rules for what constitutes a valid SBOL document, new role fields to simplify the expression of sequence features and how components are used in context, and new best practices descriptions to improve the exchange of basic sequence topology information and the description of genetic design provenance, as well as miscellaneous other minor improvements.

scholarly journals Synthetic Biology Open Language (SBOL) Version 2.2.0

2018 ◽  
Vol 15 (1) ◽  
Author(s):  
Robert Sidney Cox ◽  
Curtis Madsen ◽  
James Alastair McLaughlin ◽  
Tramy Nguyen ◽  
Nicholas Roehner ◽  
...  
Keyword(s):  
Metabolic Engineering ◽  
Synthetic Biology ◽  
Molecular Biology ◽  
Data Model ◽  
Special Issue ◽  
Biological Design ◽  
New Class ◽  
Exchange Of Information ◽  
Design Build ◽  
Synthetic Biology Open Language

AbstractSynthetic biology builds upon the techniques and successes of genetics, molecular biology, and metabolic engineering by applying engineering principles to the design of biological systems. The field still faces substantial challenges, including long development times, high rates of failure, and poor reproducibility. One method to ameliorate these problems would be to improve the exchange of information about designed systems between laboratories. The synthetic biology open language (SBOL) has been developed as a standard to support the specification and exchange of biological design information in synthetic biology, filling a need not satisfied by other pre-existing standards. This document details version 2.2.0 of SBOL that builds upon version 2.1.0 published in last year’s JIB special issue. In particular, SBOL 2.2.0 includes improved description and validation rules for genetic design provenance, an extension to support combinatorial genetic designs, a new class to add non-SBOL data as attachments, a new class for genetic design implementations, and a description of a methodology to describe the entire design-build-test-learn cycle within the SBOL data model.

scholarly journals Synthetic Biology Open Language Visual (SBOL Visual) Version 2.0

2018 ◽  
Vol 15 (1) ◽  
Author(s):  
Robert Sidney Cox ◽  
Curtis Madsen ◽  
James McLaughlin ◽  
Tramy Nguyen ◽  
Nicholas Roehner ◽  
...  
Keyword(s):  
Synthetic Biology ◽  
Best Practices ◽  
Molecular Species ◽  
Data Model ◽  
Functional Relationships ◽  
Version 2.0 ◽  
Synthetic Biology Open Language ◽  
And Function ◽  
The Relationship ◽  
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 2.0 of SBOL Visual, which builds on the prior SBOL Visual 1.0 standard by expanding diagram syntax to include functional interactions and molecular species, making the relationship between diagrams and the SBOL data model explicit, supporting families of symbol variants, clarifying a number of requirements and best practices, and significantly expanding the collection of diagram glyphs.

scholarly journals Synthetic Biology Open Language (SBOL) Version 2.3

2019 ◽  
Vol 16 (2) ◽  
Author(s):  
Curtis Madsen ◽  
Angel Goñi Moreno ◽  
Umesh P ◽  
Zachary Palchick ◽  
Nicholas Roehner ◽  
...  
Keyword(s):  
Experimental Data ◽  
Metabolic Engineering ◽  
Systems Biology ◽  
Synthetic Biology ◽  
Molecular Biology ◽  
Special Issue ◽  
Design Elements ◽  
Biological Design ◽  
Support Organization ◽  
Synthetic Biology Open Language

AbstractSynthetic biology builds upon the techniques and successes of genetics, molecular biology, and metabolic engineering by applying engineering principles to the design of biological systems. The field still faces substantial challenges, including long development times, high rates of failure, and poor reproducibility. One method to ameliorate these problems is to improve the exchange of information about designed systems between laboratories. The synthetic biology open language (SBOL) has been developed as a standard to support the specification and exchange of biological design information in synthetic biology, filling a need not satisfied by other pre-existing standards. This document details version 2.3.0 of SBOL, which builds upon version 2.2.0 published in last year’s JIB Standards in Systems Biology special issue. In particular, SBOL 2.3.0 includes means of succinctly representing sequence modifications, such as insertion, deletion, and replacement, an extension to support organization and attachment of experimental data derived from designs, and an extension for describing numerical parameters of design elements. The new version also includes specifying types of synthetic biology activities, unambiguous locations for sequences with multiple encodings, refinement of a number of validation rules, improved figures and examples, and clarification on a number of issues related to the use of external ontology terms.

scholarly journals Synthetic biology open language (SBOL) version 3.0.0

2020 ◽  
Vol 17 (2-3) ◽  
Author(s):  
Hasan Baig ◽  
Pedro Fontanarrosa ◽  
Vishwesh Kulkarni ◽  
James Alastair McLaughlin ◽  
Prashant Vaidyanathan ◽  
...  
Keyword(s):  
Synthetic Biology ◽  
Data Model ◽  
Experimental Measurements ◽  
Structural Constraint ◽  
Software Developers ◽  
Biological Design ◽  
Intended Behavior ◽  
Exchange Information ◽  
Synthetic Biology Open Language ◽  
Sequence Constraints

AbstractSynthetic biology builds upon genetics, molecular biology, and metabolic engineering by applying engineering principles to the design of biological systems. When designing a synthetic system, synthetic biologists need to exchange information about multiple types of molecules, the intended behavior of the system, and actual experimental measurements. The Synthetic Biology Open Language (SBOL) has been developed as a standard to support the specification and exchange of biological design information in synthetic biology, following an open community process involving both wet bench scientists and dry scientific modelers and software developers, across academia, industry, and other institutions. This document describes SBOL 3.0.0, which condenses and simplifies previous versions of SBOL based on experiences in deployment across a variety of scientific and industrial settings. In particular, SBOL 3.0.0, (1) separates sequence features from part/sub-part relationships, (2) renames Component Definition/Component to Component/Sub-Component, (3) merges Component and Module classes, (4) ensures consistency between data model and ontology terms, (5) extends the means to define and reference Sub-Components, (6) refines requirements on object URIs, (7) enables graph-based serialization, (8) moves Systems Biology Ontology (SBO) for Component types, (9) makes all sequence associations explicit, (10) makes interfaces explicit, (11) generalizes Sequence Constraints into a general structural Constraint class, and (12) expands the set of allowed constraints.

scholarly journals Synthetic biology open language visual (SBOL visual) version 3.0

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Hasan Baig ◽  
Pedro Fontanarossa ◽  
James McLaughlin ◽  
James Scott-Brown ◽  
Prashant Vaidyanathan ◽  
...  
Keyword(s):  
Nucleic Acid ◽  
Synthetic Biology ◽  
Molecular Species ◽  
Data Model ◽  
Structure And Function ◽  
Sequence Features ◽  
Functional Relationships ◽  
Synthetic Biology Open Language ◽  
And Function ◽  
Biological Organisms

Abstract People who engineer biological organisms often find it useful to draw diagrams in order to communicate both the structure of the nucleic acid sequences that they are engineering and the functional relationships between sequence features and other molecular species. Some typical practices and conventions have begun to emerge for such diagrams. SBOL Visual aims to organize and systematize such conventions in order to produce a coherent language for expressing the structure and function of genetic designs. This document details version 3.0 of SBOL Visual, a new major revision of the standard. The major difference between SBOL Visual 3 and SBOL Visual 2 is that diagrams and glyphs are defined with respect to the SBOL 3 data model rather than the SBOL 2 data model. A byproduct of this change is that the use of dashed undirected lines for subsystem mappings has been removed, pending future determination on how to represent general SBOL 3 constraints; in the interim, this annotation can still be used as an annotation. Finally, deprecated material has been removed from collection of glyphs: the deprecated “insulator” glyph and “macromolecule” alternative glyphs have been removed, as have the deprecated BioPAX alternatives to SBO terms.

Proposed Data Model for the Next Version of the Synthetic Biology Open Language

2014 ◽  
Vol 4 (1) ◽  
pp. 57-71 ◽  
Author(s):  
Nicholas Roehner ◽  
Ernst Oberortner ◽  
Matthew Pocock ◽  
Jacob Beal ◽  
Kevin Clancy ◽  
...  
Keyword(s):  
Synthetic Biology ◽  
Data Model ◽  
Synthetic Biology Open Language

System development informing staff on the causes and consequences of equipment failures

2018 ◽  
pp. 49-55
Author(s):  
V. A. Azev ◽  
I. N. Sukharkov ◽  
V. I. Arikulov ◽  
V. Yu. Zalyadnov ◽  
V. A. Khazhiev
Keyword(s):  
Best Practices ◽  
System Development ◽  
Transport Equipment ◽  
Exchange Of Information ◽  
Equipment Failures

The Exchange of information on the results of the functioning of the systems to ensure the efficiency of the equipment within the company, Association or enterprise is an important component of production activities. Properly organized exchange of information about the causes of failures and malfunctions of equipment, as well as best practices and effective solutions to ensure the efficiency of equipment allows without significant investments to improve the efficiency and safety of production. The purpose of this article is to describe the work carried out in LLC «SUEKKhakassia» to improve the efficiency of development and development of solutions aimed at improving the performance of mining and transport equipment.

scholarly journals The first 10 years of the international coordination network for standards in systems and synthetic biology (COMBINE)

2020 ◽  
Vol 17 (2-3) ◽  
Author(s):  
Dagmar Waltemath ◽  
Martin Golebiewski ◽  
Michael L Blinov ◽  
Padraig Gleeson ◽  
Henning Hermjakob ◽  
...  
Keyword(s):  
Synthetic Biology ◽  
Data Model ◽  
Computational Models ◽  
Life Sciences ◽  
The Past ◽  
Challenges And Opportunities ◽  
Stakeholder Workshop ◽  
Software Engineers ◽  
Future Work ◽  
Modeling In Biology

AbstractThis paper presents a report on outcomes of the 10th Computational Modeling in Biology Network (COMBINE) meeting that was held in Heidelberg, Germany, in July of 2019. The annual event brings together researchers, biocurators and software engineers to present recent results and discuss future work in the area of standards for systems and synthetic biology. The COMBINE initiative coordinates the development of various community standards and formats for computational models in the life sciences. Over the past 10 years, COMBINE has brought together standard communities that have further developed and harmonized their standards for better interoperability of models and data. COMBINE 2019 was co-located with a stakeholder workshop of the European EU-STANDS4PM initiative that aims at harmonized data and model standardization for in silico models in the field of personalized medicine, as well as with the FAIRDOM PALs meeting to discuss findable, accessible, interoperable and reusable (FAIR) data sharing. This report briefly describes the work discussed in invited and contributed talks as well as during breakout sessions. It also highlights recent advancements in data, model, and annotation standardization efforts. Finally, this report concludes with some challenges and opportunities that this community will face during the next 10 years.

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