EAGER: A Standard Enabled Workflow for Synthetic Biology

EAGER：合成生物学的标准工作流程

• 批准号: 1748200
• 负责人: Chris Myers
• 金额: $ 15万
• 依托单位: University of Utah
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-15 至 2020-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1748200&HistoricalAwards=false
• 关键词: EAGER; Standard; Enabled; Workflow; Synthetic

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.

合成生物学工作流由提供遗传部分信息的数据存储库、将这些部分组成电路的序列级设计工具和构建和分析完整设计模型的系统级设计工具组成。数据标准支持在这样的工作流中随时交换信息。它们允许从各种来源连接存储库和工具。该工作流将利用为系统和合成生物学开发的几个数据标准。该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。该项目还将与期刊合作，特别是ACS合成生物学，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，以尽量减少对他们的影响。最终，这个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中发挥重要作用。这个支持标准的工作流将利用各种数据标准。这些标准包括可用于描述和可视化遗传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），可用于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COMBINE Archive。使用这些标准，将构建一个合成生物学工作流程，其中包括多个存储库，如纽卡斯尔SynBioHub和JBEI ICE存储库，以及多个软件工具，如Benchling， sholdesigner， iBioSim和Cello等。本项目的智力价值包括以下活动：-整合和改进来自各种库的遗传部分数据集，其中包括iGEM注册表，MIT Cello转录电路库和Newcastle BacillOndex部分库。-改善SynBioHub与远程存储库的连接，如Benchling， JBEI ICE和sholme，作为基因设计信息的进一步来源。-连接软件以形成合成生物学工作流程，其中包括sholdesigner， iBioSim和SynBioHub。——应用和验证该工作流，以多细胞时空模式的遗传电路设计和通信电路的计算建模为驱动示例。

项目成果

Extending SynBioHub’s Functionality with Plugins

使用插件扩展 SynBioHub 的功能

• DOI: 10.1021/acssynbio.0c00056
• 发表时间: 2020
• 期刊: ACS Synthetic Biology
• 影响因子: 4.7
• 作者: Mante, Jeanet;Zundel, Zach;Myers, Chris
• 通讯作者: Myers, Chris

Design of Asynchronous Genetic Circuits

• DOI: 10.1109/jproc.2019.2916057
• 发表时间: 2019-06
• 期刊: Proceedings of the IEEE
• 影响因子: 20.6
• 作者: Tramy Nguyen;Timothy S. Jones;P. Fontanarrosa;Jeanet V. Mante;Z. Zundel;D. Densmore;C. Myers

iBioSim 3: A Tool for Model-Based Genetic Circuit Design

• DOI: 10.1021/acssynbio.8b00078
• 发表时间: 2019-07-01
• 期刊: ACS SYNTHETIC BIOLOGY
• 影响因子: 4.7
• 作者: Watanabe, Leandro;Tramy Nguyen;Myers, Chris
• 通讯作者: Myers, Chris

STAMINA: STochastic Approximate Model-checker for INfinite-state Analysis

• DOI: 10.1007/978-3-030-25540-4_31
• 发表时间: 2019-06
• 期刊: ArXiv
• 作者: Thakur Neupane;C. Myers;C. Madsen;Hao Zheng;Zhen Zhang

Dynamic Flux Balance Analysis Models in SBML

• DOI: 10.1101/245076
• 发表时间: 2018-01
• 期刊: bioRxiv
• 作者: Leandro H. Watanabe;M. König;C. Myers