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From data to knowledge / the ONDEX System for integrating Life Sciences data sources

从数据到知识/用于集成生命科学数据源的 ONDEX 系统

基本信息

批准号：
BB/F006039/1
负责人：
Christopher Rawlings
金额：
$ 146.29万
依托单位：
Rothamsted Research
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2008
资助国家：
英国
起止时间：
2008 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=BB%2FF006039%2F1
关键词：
data knowledge ONDEX System integrating

项目摘要

The biological sciences generate many different types of data from different specialist disciplines (e.g. genetics, biochemistry, molecular biology). Bringing data together coherently is a major undertaking in any systems biology project. While new databases of biological thesauri and classification systems (ontologies) for the component parts of biology make it easier to link specialist databases, this only solves part of the problem of data integration for systems biologists who need a much richer body of information. For example, there are many different ways that biological components can be related (e.g. by function, location, size) which needs to be captured and information about the provenance (history or source) of data can be important when it is interpreted. New types of information are also important in systems biology, including descriptions of the biological processes and pathways for metabolism and information flow. Many of these have been created by extracting information from the scientific literature to form the basis for the predictive dynamic models and simulations of system function. Because systems biology has a need for complex data integration and scientific text mining that is not met by readily available bioinformatics software in the biological research community, a prototype system (ONDEX) has been developed by Rothamsted Research. This project will combine ONDEX with leading technologies in workflow, graph analysis and text mining, to develop a powerful and professional tool that will underpin systems biology research. Three systems biology research projects, run by our BBSRC-funded systems biology centre partners, will drive the development of ONDEX and will validate new features on real scientific problems. Biological areas addressed cover: bioenergy crops; yeast metabolome models; and Telomere Function in ageing. The research partners bring important technical expertise that will enhance ONDEX with new capabilities known to be required by systems biologists at their centres. These include: * Extensions to methods that map data into ONDEX to broaden the range of data that can be integrated and capture more of the information about it (the metadata). * State of the art text mining capabilities, for extracting biological concepts and relationships from online text to enable new data buried in the scientific literature to be extracted and structured into models and databases. * Extensions to handle the statistical uncertainty inherent in many biological relationships, to enable new relationships to be identified in the integrated datasets using modern statistical inference techniques. * Enhanced graphical visualisations of the complex network of relationships to accommodate new information and scale to huge data networks, to enable a better understanding of new interactions, and better ways of interrogating the data in a richly integrated dataset * Exploitation of the latest in distributed computing techniques and scientific workflows to simplify, automate and scale the complex task of integration. * Extended range of data interfaces relevant to both programmers and users to enable shared access over the Internet of the integrated datasets, which are important information resources in their own right. A number of actions and engineering developments will make ONDEX easier to use by biologists and support uptake in new areas of systems biology. These include new training resources, workshops for users and developers and providing direct help for new applications through an outreach programme. At the end of the project ONDEX will be delivered in a well-engineered and robust form to existing and new users that will be more readily used by a greatly expanded user and developer community that should make it sustainable in the long term as an open software project.

生物科学从不同的专业学科（例如遗传学、生物化学、分子生物学）生成许多不同类型的数据。将数据连贯地汇集在一起是任何系统生物学项目的主要任务。虽然生物学组成部分的生物学叙词表和分类系统（本体论）的新数据库使连接专业数据库变得更容易，但这只解决了需要更丰富信息的系统生物学家的部分数据集成问题。例如，有许多不同的方式可以使需要被捕获的生物组分相关（例如，通过功能、位置、大小），并且关于数据的起源（历史或来源）的信息在解释时可能是重要的。新类型的信息在系统生物学中也很重要，包括对新陈代谢和信息流的生物过程和途径的描述。其中许多是通过从科学文献中提取信息来创建的，以形成预测动态模型和系统功能模拟的基础。由于系统生物学需要复杂的数据集成和科学文本挖掘，而生物研究界现有的生物信息学软件无法满足这一需求，因此Rothamsted Research开发了一个原型系统（ONDEX）。该项目将联合收割机ONDEX与工作流、图形分析和文本挖掘方面的领先技术相结合，开发一个强大而专业的工具，为系统生物学研究提供基础。由我们的BBSRC资助的系统生物学中心合作伙伴运行的三个系统生物学研究项目将推动ONDEX的发展，并将验证真实的科学问题的新功能。生物领域涉及：生物能源作物;酵母代谢组模型;和端粒功能老化。研究合作伙伴带来了重要的技术专长，将增强ONDEX的新功能，这些功能是系统生物学家在其中心所需的。其中包括：* 对将数据映射到ONDEX的方法进行扩展，以扩大可以集成的数据范围，并捕获更多关于它的信息（元数据）。* 最先进的文本挖掘功能，用于从在线文本中提取生物学概念和关系，以使隐藏在科学文献中的新数据能够被提取并构建到模型和数据库中。* 扩展来处理许多生物关系中固有的统计不确定性，使新的关系能够使用现代统计推断技术在集成数据集中识别。* 增强了复杂关系网络的图形可视化，以适应新信息并扩展到庞大的数据网络，从而更好地理解新的交互，并以更好的方式在高度集成的数据集中查询数据 * 利用最新的分布式计算技术和科学工作流来简化、自动化和扩展复杂的集成任务。* 扩大与程序员和用户有关的数据接口范围，以便能够通过互联网共享综合数据集，这些数据集本身就是重要的信息资源。一些行动和工程开发将使ONDEX更容易被生物学家使用，并支持系统生物学新领域的吸收。其中包括新的培训资源、为用户和开发人员举办的讲习班以及通过外联方案为新的应用程序提供直接帮助。在项目结束时，ONDEX将以精心设计和强大的形式交付给现有和新用户，这将更容易被大大扩展的用户和开发人员社区使用，这将使其作为一个开放的软件项目长期可持续发展。

项目成果

期刊论文数量（10）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Named entity recognition for bacterial Type IV secretion systems.

DOI：
10.1371/journal.pone.0014780
发表时间：
2011-03-29
期刊：
PloS one
影响因子：
3.7
作者：
Ananiadou S;Sullivan D;Black W;Levow GA;Gillespie JJ;Mao C;Pyysalo S;Kolluru B;Tsujii J;Sobral B
通讯作者：
Sobral B

Getting the best of Linked Data and Property Graphs: rdf2neo and the KnetMiner Use Case

充分利用链接数据和属性图：rdf2neo 和 KnetMiner 用例