EAGER: A Standard Enabled Workflow for Synthetic Biology

合成生物学工作流程由提供有关遗传部件信息的数据库、将这些部件组成电路的序列级设计工具以及构建和分析完整设计模型的系统级设计工具组成。数据标准允许在这样的工作流程中随时交换信息。它们允许从不同来源连接存储库和工具。这一工作流程将利用为系统和合成生物学开发的几个数据标准。这一工作流程将对合成生物学用户的几个不同社区产生更广泛的影响。该项目还将与期刊，特别是ACS合成生物学合作，将这一工作流程整合到他们的数据存档过程中，并将为作者提供培训视频，以将对他们的影响降至最低。归根结底，这一工作流程应该在使合成生物学成为一项真正可复制的科学努力方面发挥重要作用。这个支持标准的工作流程将利用各种数据标准。这些标准包括可用于描述和可视化基因设计的合成生物学开放语言(SBOL)、可用于创建计算模型的系统生物学标记语言(SBML)、可描述模拟实验的模拟实验描述标记语言(SED-ML)以及可将这些文件组合成单个可交换文档的组合档案。使用这些标准，将构建一个合成生物学工作流程，其中包括多个储存库，如NewCastle SynBioHub和JBEI ICE储存库，以及多个软件工具，如Benchling、SBOLDesigner、iBioSim和Cello等。该项目的学术价值包括以下活动：--整合和改进来自各种库的遗传部件数据库，其中包括iGEM注册表、麻省理工学院Cello转录电路库和纽卡斯尔BacillOndex零件库。--改善SynBioHub与诸如Benchling、JBEI ICE和SBOLme等远程储存库的连接，作为遗传设计信息的进一步来源。--软件的连接以形成合成生物学工作流程，其中包括SBOLDesigner、iBioSim和SynBioHub。--这一工作流程的应用和验证以多细胞时空构图的通信电路的遗传电路设计和计算建模为驱动范例。

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, and system-level design tools to construct and analyze models of complete designs. Data standards enable the ready exchange of information within such a workflow. They allow repositories and tools to be connected from a diversity of sources. This workflow will leverage several data standards developed for systems and synthetic biology. This workflow will have a broader impact on several diverse communities of synthetic biology users. This project also will work with journals, especially ACS Synthetic Biology, to integrate this workflow into their data archival process, and it will provide training videos for authors to minimize the impact on them. Ultimately, this workflow should play a significant role in enabling synthetic biology to become a truly reproducible scientific endeavor. This standard enabled workflow will leverage a variety of data standards. These standards include the Synthetic Biology Open Language (SBOL), which can be utilized to describe and visualize genetic designs, the Systems Biology Markup Language (SBML), which can be used to create computational models, the Simulation Experiment Description Markup Language (SED-ML), which can describe simulation experiments, and the COMBINE Archive, which can combine these files into a single exchangeable document. Using these standards, a synthetic biology workflow will be constructed that includes multiple repositories, such as the Newcastle SynBioHub and the JBEI ICE Repository, and multiple software tools such as Benchling, SBOLDesigner, iBioSim, and Cello, among others. The intellectual merit of this project includes the following activities:--Integration and refinement of genetic part datasets from a variety of libraries, including, among others, the iGEM registry, MIT Cello transcriptional circuit library, and the Newcastle BacillOndex part library. --Improve SynBioHub's connections with remote repositories, such as Benchling, JBEI ICE, and SBOLme, as further sources for genetic design information.--Connection of software to form a synthetic biology workflow, including, among others, SBOLDesigner, iBioSim, and SynBioHub.--Application and validation of this workflow using as a driving example the genetic circuit design and computational modeling of communication circuits for multicellular spatiotemporal patterning.