SysMO-DB2

系统管理数据库2

• 批准号: BB/I004637/1
• 负责人: Carole Goble
• 金额: $ 121.08万
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2010
• 资助国家: 英国
• 起止时间: 2010 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FI004637%2F1
• 关键词: SysMO; DB2

Systems biology is a biology-based inter-disciplinary study field combining experimental investigations and computational modeling to discover emergent properties of complex interactions in biological systems. SysMO is a European trans-national funding and research initiative on 'Systems Biology of Microorganisms'. The initiative's goal is to record and describe the dynamic molecular processes that occur in microorganisms in a comprehensive way and to present these processes in the form of computerized mathematical models. Each project is made up of a consortium of European institutions and each works towards different research outcomes on a variety of microorganisms, including bacteria, archaea (single-celled microorganisms) and yeast. The environmental conditions for each organism vary, growing in culture, soil, water and animal hosts. This diversity means that there are many different kinds of models and many different types of data collected. The SysMO initiative has been divided into two phases: SysMO1 funded eleven projects and 91 institutions; SysMO2 will fund seven projects, five of which are project continuations from phase 2 (so six projects are concluded) and two of which are new. The research outcomes (models, data, procedures), and the know-how and best practice developed by the scientists, are to be managed and pooled in order to: benefit the members of the programme during the running of the projects; disseminate and publish the results to the wider scientific community; and safeguard the results after the completion of the projects that maximises the 'shelf life' and utility of data generated by SysMO. SysMO-DB is a project to build and manage an incrementally developed web-based software platform to achieve this. SysMO-DB1, funded during the first phase, begun the development of a web-based platform - called the SEEK - for cataloguing the different outcomes of the projects, archiving data, procedures and models and integrating with the different project's local data management systems, including the standardisation of the information used to describe the data and models and the handling of project spreadsheets. The SEEK also includes a social network for the SysMO members and integrates with public repositories for data, models, analyses and publications such as JWS Online (for models); SABIO-RK (for data), myExperiment (for bioinformatics data analysis pipelines) and PubMed (for publications). SysMO-DB has also developed effective practices for working with SysMO scientists through the founding of a PALs focus group of researchers who shape the developments, data standards and protocols necessary for pooling and promote SEEK adoption in their own projects. The focus of SysMO-DB1 is on supporting the current projects. SysMO-DB2 continues and extends the work to cope with SysMO-phase changes and life after beyond and after SysMO: new and terminating projects, personnel change, publication outside the consortium and long-term preservation of results. SysMO-DB2 also plans to package up the software and methods so that they can be adopted and sustained by other programmes such as EraSysBio+. EraSysBio+ is a pan-European programme for 16 Systems Biology projects. It is similar in organisation to SysMO but radically different in terms of scope. Hence it differs in the data, model and process capabilities needed. As part of widening the adoption of the SysMO-DB approach the project will support EraSysBio+ in its first 18 months. The two projects from EraSysBio+ that focus on microorganisms will be fully integrated into the SysMO-DB work programme. For the full range of EraSysBio+ projects SysMO-DB2 will instantiate a new instance of the SEEK, provide advice and help launch a PALs scheme.

系统生物学是一个基于生物学的跨学科研究领域，结合实验研究和计算建模，以发现生物系统中复杂相互作用的涌现特性。SysMO是一个欧洲跨国资助和研究“微生物系统生物学”的倡议。该倡议的目标是以全面的方式记录和描述微生物中发生的动态分子过程，并以计算机化数学模型的形式呈现这些过程。每个项目都由一个欧洲机构联盟组成，每个项目都致力于对各种微生物的不同研究成果，包括细菌，古生菌（单细胞微生物）和酵母。每种生物的环境条件各不相同，在培养物、土壤、水和动物宿主中生长。这种多样性意味着有许多不同类型的模型和收集的许多不同类型的数据。SysMO倡议分为两个阶段：SysMO 1资助了11个项目和91个机构; SysMO 2将资助7个项目，其中5个是第2阶段的项目延续（因此6个项目已经完成），其中2个是新项目。的研究成果（模型、数据、程序）以及科学家开发的专门知识和最佳做法，以便：在项目运行期间使方案成员受益;向更广泛的科学界传播和出版成果;并在项目完成后保护结果，最大限度地延长SysMO生成的数据的“保存期限”和效用。SysMO-DB是一个构建和管理增量开发的基于Web的软件平台的项目，以实现这一目标。在第一阶段得到资助的SysMO-DB 1开始开发一个基于网络的平台-称为SEEK -用于对项目的不同成果进行编目，将数据、程序和模型存档，并与不同项目的本地数据管理系统集成，包括用于描述数据和模型的信息的标准化以及项目电子表格的处理。SEEK还包括SysMO成员的社交网络，并与数据，模型，分析和出版物的公共存储库集成，如JWS Online（用于模型）; SABIO-RK（用于数据），myExperiment（用于生物信息学数据分析管道）和PubMed（用于出版物）。SysMO-DB还开发了与SysMO科学家合作的有效实践，通过建立帕尔斯研究小组，这些研究人员塑造了汇集和促进SEEK在自己项目中采用所需的开发，数据标准和协议。SysMO-DB 1的重点是支持当前的项目。SysMO-DB2继续并扩展了工作，以科普SysMO阶段的变化和SysMO之后的生活：新的和终止的项目，人员变更，联盟外的出版物和长期保存结果。SysMO-DB2还计划将软件和方法打包，以便它们可以被EraSysBio+等其他程序采用和维护。EraSysBio+是一个泛欧洲计划，包含16个系统生物学项目。它在组织上与SysMO相似，但在范围上完全不同。因此，它在所需的数据、模型和流程能力方面有所不同。作为扩大采用SysMO-DB方法的一部分，该项目将在前18个月内支持EraSysBio+。来自EraSysBio+的两个专注于微生物的项目将完全整合到SysMO-DB工作计划中。对于所有的EraSysBio+项目，SysMO-DB2将实例化一个新的SEEK实例，提供建议并帮助启动帕尔斯方案。

项目成果

Phosphoglycerate kinase acts as a futile cycle at high temperature.

磷酸甘油酸激酶在高温下充当无效循环。

• DOI: 10.1099/mic.0.000542
• 发表时间: 2017
• 期刊: Microbiology (Reading, England)
• 作者: Kouril T

Determining enzyme kinetics for systems biology with nuclear magnetic resonance spectroscopy.

通过核磁共振光谱确定用于系统生物学的酶动力学。

• DOI: 10.3390/metabo2040818
• 发表时间: 2012-11-06
• 期刊: Metabolites
• 影响因子: 4.1
• 作者: Eicher JJ;Snoep JL;Rohwer JM
• 通讯作者: Rohwer JM

Why linked data is not enough for scientists

• DOI: 10.1016/j.future.2011.08.004
• 发表时间: 2013-02-01
• 期刊: FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
• 影响因子: 7.5
• 作者: Bechhofer, Sean;Buchan, Iain;Goble, Carole
• 通讯作者: Goble, Carole

FAIRDOM approach for semantic interoperability of systems biology data and models

用于系统生物学数据和模型语义互操作性的 FAIRDOM 方法

• 发表时间: 2016
• 期刊: CEUR Workshop Proceedings
• 作者: Krebs O.

The evolution of standards and data management practices in systems biology.

• DOI: 10.15252/msb.20156053
• 发表时间: 2015-12-23
• 期刊: Molecular systems biology
• 影响因子: 9.9
• 作者: Stanford NJ;Wolstencroft K;Golebiewski M;Kania R;Juty N;Tomlinson C;Owen S;Butcher S;Hermjakob H;Le Novère N;Mueller W;Snoep J;Goble C
• 通讯作者: Goble C