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From data to knowledge – the Ondex System for integrating Life Sciences data sources

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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 Presentation Transcript

  • From data to knowledge – the ONDEX System for integrating Life Sciences data sources C. Rawlings1, A. Karp1, C. Goble2, R. Stevens2, S. Ananiadou2, D. Kell3, A. Wipat4, D. Wilkinson4, P. Lord4, D. Lydall4 , C. Canevet1 1Rothamsted Research, Harpenden; 2University of Manchester, School of Computer Science; 3University of Manchester, School of Chemistry & Manchester Centre for Integrative Systems Biology; 4Newcastle University, Centre for Integ Summary Demonstrator Projects Bioenergy crop improvement Yeast metabolome models • Funded under SABR initiative (2008-2011) • Identify new genetic and molecular targets to http://www.biomass4energy.org http://www.mcisb.org/research.html improve bioenergy crops (Rothamsted) Different metabolic networks • Create a robust, extensible data integration • Integrate different yeast metabolome models system for supporting systems biology (Manchester) research. • Support studies of telomere function relating • Extend the ONDEX data integration to ageing research in yeast (Newcastle). platform and support four demonstrator • Support studies of signalling pathways projects involving three CISB centres. controlling circadian rhythms (Edinburgh) ONDEX data integration platform Data Input Data Integration Data Analysis Data alignment methods Data Integration (ONDEX) (e.g. accession based OVTK Biological Databases mapping, BLAST mapping) Telomere function relating to ageing http://www.cisban.ac.uk/aims.html Graph of Concepts & Consensus metabolic network Importer Relations Query API Protein Networks Experimental Data OVTK2 Importer New Insights XML Export Technology Development & Project Overview Ontologies & Free Text r W eb • Extend core data structures, interfaces and data rte se Im po rv ice s integration framework to support probabilistic NaCTeM text mining relationships. • Adapt NaCTeM text mining tools to use semantic lexicon ontology Parses Natural Language Processing parsing to extract more complex relationships from deep raw part-of-speech annotated named entity syntactic (unstructured) Tagging (structured) recognition Parsing text GENIA text ENJU bio-text sources. • Upgrade the workflow management to incorporate The ONDEX system stores data as a graph of Concepts and Relations. Concepts represent data new developments from myGrid. entities and Relations link these entities together. Additional semantic annotation is added using • Develop the user interfaces and other components concept classes, relation types, evidences and controlled vocabularies. Data is imported by data to support comparative analyses. source specific parsers. Mapping methods create new Relations between Concepts. Local and • Exploit new data structures with statistical data global consistency checks are performed. Data integration can be configured and executed using analysis methods and associated visualization web services via Taverna. (http://taverna.sourceforge.net). The ONDEX system is open source methods. and written in JAVA. It can be obtained at http://ondex.sf.net.