From data to knowledge: the ONDEX System for integrating life sciences data resources

Completed

Not Energy Related
Renewable Energy Sources(Bio-Energy, Other bio-energy)

Basic and strategic applied research

BIOLOGICAL AND AGRICULTURAL SCIENCES (Biological Sciences)
PHYSICAL SCIENCES AND MATHEMATICS (Computer Science and Informatics)

Not Cross-cutting

Prof C Rawlings
Computational and Systems Biology
Rothamsted Research

Institute Project

BBSRC

01 April 2008

30 November 2011

44 months

£303,459

Pharmaceuticals and Biotechnology

East of England

Prof C Rawlings, Computational and Systems Biology, Rothamsted Research

Thee grants are Linked BB/F006039/1, BB/F006063/1 and BBS/E/C/00004918.

The aim of this project is to develop an extensible data integration system for supporting systems biology research. The project will extend the ONDEX data integration platform (http://ondex.sf.net) and support four demonstrator projects at three Centres for Integrated Systems Biology (CISB). The demonstrator projects represent a range of general data integration problems in systems biology and will exercise and validate new features through direct interaction with end-users. The three core demonstrator projects will: identify new genetic and molecular targets to improve bioenergy crops (Rothamsted); integrate, and validate different yeast metabolome models (Manchester, MCISB) and support studies of telomere function relating to ageing research in yeast (Newcastle, CISBAN). A fourth demonstrator project at the CSBE (Edinburgh) will study signal transduction processes controlling circadian rhythms in Arabidopsis thaliana. The ONDEX system has been developed as a generic solution to semantic integration of life science data using a warehousing approach based on a generic graph data structure. Integration is achieved by a set of mapping functions that populate the data graph with additional equivalence relationships. The parsing and mapping features implemented in ONDEX enable a wide range of data to be integrated including sequence databases, microarray information, transcription factor databases (e.g. Transfac), biological pathway databases (e.g. KEGG), gene function and biological ontologies (e.g. from the OBO foundry). In addition there are mapping functions that implement text mining features. During this project, new features and improvements will be made to increase the range of system biology projects that can be supported. An important part of the project will be to provide outreach and support to new users and a key objective will be to engage with a wider range of BBSRC-funded systems biology projects.

30/09/13