From data to knowledge / the ONDEX System for integrating Life Sciences data sources
From data to knowledge / the ONDEX System for integrating Life Sciences data sources
批准号:
BB/F006039/1
负责人:
Christopher Rawlings
金额:
$146.29万
依托单位:
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
项目状态:
已结题
起止时间:
2008 至 --
中文摘要
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英文摘要
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.
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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
DOI:
10.6084/m9.figshare.7314323.v1
发表时间:
2018
期刊:
影响因子:
--
作者:
[Brandizi M]
通讯作者:
Brandizi M
Semantic Web applications and tools for the life sciences: SWAT4LS 2010.
生命科学语义 Web 应用程序和工具:SWAT4LS 2010。
DOI:
10.1186/1471-2105-13-s1-s1
发表时间:
2012
期刊:
BMC bioinformatics
影响因子:
3
作者:
[Burger A]
通讯作者:
Burger A
DOI:
10.1080/15427951.2011.604548
发表时间:
2011-01-01
期刊:
INTERNET MATHEMATICS
影响因子:
--
作者:
[Alcaraz, Nicolas, Kuecuek, Hande, Baumbach, Jan]
通讯作者:
Baumbach, Jan
DOI:
10.1093/bioinformatics/btw731
发表时间:
2017-04-01
期刊:
Bioinformatics (Oxford, England)
影响因子:
--
作者:
[Balaur I, Mazein A, Saqi M, Lysenko A, Rawlings CJ, Auffray C]
通讯作者:
Auffray C
共 7 条
QTLNetMiner: Mining Candidate Gene Networks From Genetic Studies of Crops and Animals
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批准号:BB/I023860/1
-
项目类别:Research Grant
-
资助金额:$12.78万
-
财政年份:2012
-
负责人:Christopher Rawlings
-
依托单位:
Biofortifying Brassica with calcium (Ca) and magnesium (Mg) for human health
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批准号:BB/G015716/1
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项目类别:Research Grant
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资助金额:$46.04万
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财政年份:2009
-
负责人:Christopher Rawlings
-
依托单位:
海外基金