COpenPlantOmics (COPO): a Collaborative Bioinformatics Plant Science Platform

COpenPlantOmics (COPO)：协作生物信息学植物科学平台

• 批准号: BB/L024055/1
• 负责人: Mario Caccamo
• 金额: $ 75.25万
• 依托单位: Earlham Institute
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2014
• 资助国家: 英国
• 起止时间: 2014 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FL024055%2F1
• 关键词: COpenPlantOmics; COPO; Collaborative; Bioinformatics; Plant

We live in a digital age where we increasingly rely on interconnected resources in our daily lives. Biological science, due to the very nature of the complexity of worldwide research avenues, is typically fragmented. Even though scientific information is published in peer-reviewed articles, it is often badly described and, until very recently, often unavailable to the general public because of journal licensing issues and expensive subscription costs. The field of bioinformatics (the analysis and management of biological data using computational methods) produces many freely available tools for data analysis and exposure that are incredibly useful to researchers. However, these tools often do not interoperate well, meaning that great effort is spent attempting to convert or tweak datasets to fit with other tools that further bioinformatics processes, hindering timely accurate reusable research. Couple this with the lack of descriptive information noted earlier, and knowledge that can be vital to one researcher, team or community can become at least unreproducible (thus letting others confirm findings) at worst unusable.Life scientists are people focused on investigating biological processes. This requires a lot of time, effort and fastidiousness in experimental observation, data collection and analysis. Typically for life scientists, more time is spent on the former: defining and publishing experimental methods and results. The latter, i.e. the data behind these results, is usually badly defined and largely unpublished. For computer scientists, the story is reversed - the focus is on getting to the data. This platform will bridge the gap between these two groups by providing tools and training to both life and computer scientists in the plant bioscience field, in order to help them get their data into the right formats and described uniformly for open research.To do this, the management, interoperability and curation of scientific datasets is key. Researchers need clear guidance and help to:- Manage their data in a concise relevant way that allows immediate reuse by others: Generating data is only one part of the picture. To back up scientific findings, data needs to be made available to others to allow the same degree of rigour and peer review that is enforced for published material. This is not an easy task because the tools and resources required to describe data well and to make data available are typically designed for the computer scientist.- Let them analyse their data easily: Large software development projects like Galaxy provide access to complex analytical tools - we are not aiming to reinvent the wheel in this regard. We aim to engage and collaborate with these existing providers to develop and exploit interfaces to these specialised software projects, so to let descriptive tools and analytical tools communicate efficiently.This project will address these issues directly, providing tools for storing, annotating and sharing valuable information as well as promoting clear guidance, training. Overall this promises to be a major boost to UK plant sciences research. This project aims to promote and build links between scientific knowledge and the tools used to generate that knowledge, addressing the lack of descriptive information about underlying data. By doing so, we will provide a platform comprising both existing tools and novel interoperability processes, allowing researchers easy access to methods of describing their work, feeding directly into analytical software, thus promoting clear and robust best practices in science.Open science is vital to the future generation of researcher, especially to realise the goals of transparent knowledge sharing. This project will remove the barriers that restrict researchers in making their findings freely available to everyone in a consolidated seamless easy-to-use fashion.

我们生活在一个数字时代，我们在日常生活中越来越依赖于相互关联的资源。由于世界范围内研究途径的复杂性，生物科学通常是分散的。尽管科学信息发表在同行评审的文章中，但往往描述得很糟糕，而且直到最近，由于期刊许可问题和昂贵的订阅费用，公众往往无法获得。生物信息学领域（使用计算方法分析和管理生物数据）产生了许多免费的数据分析和暴露工具，对研究人员非常有用。然而，这些工具通常不能很好地互操作，这意味着需要花费大量精力来转换或调整数据集，以适应其他工具，从而进一步促进生物信息学过程，从而阻碍了及时准确的可重用研究。再加上前面提到的描述性信息的缺乏，对一个研究人员、团队或社区至关重要的知识至少可能变得不可复制（从而让其他人确认发现），最坏的情况是无法使用。这需要大量的时间、精力和细致的实验观察、数据收集和分析。通常对于生命科学家来说，更多的时间花在前者上：定义和发表实验方法和结果。后者，即这些结果背后的数据，通常定义不清，而且基本上没有公布。对于计算机科学家来说，情况正好相反--重点是获取数据。该平台将通过为植物生物科学领域的生命科学家和计算机科学家提供工具和培训来弥合这两个群体之间的差距，以帮助他们将数据转换为正确的格式并统一描述以进行开放研究。为此，科学数据集的管理，互操作性和策展是关键。研究人员需要明确的指导和帮助：-以简洁相关的方式管理他们的数据，允许其他人立即重用：生成数据只是其中的一部分。为了支持科学发现，需要向其他人提供数据，以允许对出版材料进行同样程度的严格和同行审查。这不是一件容易的事，因为描述数据和提供数据所需的工具和资源通常是为计算机科学家设计的。让他们轻松分析数据：像Galaxy这样的大型软件开发项目提供了对复杂分析工具的访问-我们的目标不是在这方面重新发明轮子。我们的目标是与这些现有的供应商合作，开发和利用这些专业软件项目的接口，使描述工具和分析工具有效地沟通。这个项目将直接解决这些问题，提供存储，注释和共享有价值的信息的工具，以及促进明确的指导，培训。总的来说，这有望成为英国植物科学研究的一大推动力。该项目旨在促进和建立科学知识与用于产生这种知识的工具之间的联系，解决缺乏关于基础数据的描述性信息的问题。通过这样做，我们将提供一个平台，包括现有的工具和新的互操作性过程，使研究人员能够轻松访问描述其工作的方法，直接输入分析软件，从而促进科学中明确和强大的最佳实践。开放科学对未来一代的研究人员至关重要，特别是实现透明知识共享的目标。该项目将消除限制研究人员以整合的无缝易用方式向每个人免费提供其研究结果的障碍。

项目成果

COPO - bridging the gap from data to publication in plant science

COPO - 弥合植物科学从数据到出版的差距

• DOI: 10.7490/f1000research.1111380.1
• 发表时间: 2016
• 期刊: F1000Research
• 作者: Anthony Etuk

COPO: a metadata platform for brokering FAIR data in the life sciences

• DOI: 10.1101/782771
• 发表时间: 2019-09
• 期刊: bioRxiv
• 作者: Anthony Etuk;Felix Shaw;Alejandra N. González-Beltrán;David Johnson;Marie-Angélique Laporte;P. Rocca-Serra;E. Arnaud;M. Devare;P. Kersey;Susanna-Assunta Sansone;Robert P. Davey

VERNALIZATION1 controls developmental responses of winter wheat under high ambient temperatures

• DOI: 10.1242/dev.172684
• 发表时间: 2019-02-01
• 期刊: DEVELOPMENT
• 影响因子: 4.6
• 作者: Dixon, Laura E.;Karsai, Ildiko;Griffiths, Simon
• 通讯作者: Griffiths, Simon

The Ontologies Community of Practice: A CGIAR Initiative for Big Data in Agrifood Systems.

• DOI: 10.1016/j.patter.2020.100105
• 发表时间: 2020-10-09
• 期刊: Patterns (New York, N.Y.)
• 作者: Arnaud E;Laporte MA;Kim S;Aubert C;Leonelli S;Miro B;Cooper L;Jaiswal P;Kruseman G;Shrestha R;Buttigieg PL;Mungall CJ;Pietragalla J;Agbona A;Muliro J;Detras J;Hualla V;Rathore A;Das RR;Dieng I;Bauchet G;Menda N;Pommier C;Shaw F;Lyon D;Mwanzia L;Juarez H;Bonaiuti E;Chiputwa B;Obileye O;Auzoux S;Yeumo ED;Mueller LA;Silverstein K;Lafargue A;Antezana E;Devare M;King B
• 通讯作者: King B

Sequencing smart: De novo sequencing and assembly approaches for non-model mammals

智能测序：非模型哺乳动物的从头测序和组装方法

• DOI: 10.1101/723890
• 发表时间: 2019
• 作者: Etherington G