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Pharmaceutical Knowledge retrieval through Reasoning of ChEMBL RDF
1. Pharmaceutical Knowledge Retrieval through Reasoning of ChEMBL RDF Background and Status Reporting Annsofie Andersson Master thesis at the department of pharmaceutical bioscience 2010-03-04
2. How is available pharmaceutical data from ChEMBL reached in an efficient way and in what way may this data be used?
3. Importance of this research – Use of data + BCR ABL BCR-ABL Kinase Cancer cells proliferate
4. Importance of this research – Use of data Cancer cells can’t proliferate Imatinib BCR-ABL Kinase + Inhibition
5. Use of data MoSS- Molecular Substructure Mining Run Moss on: 1. On bioactive compounds between two protein families 2. On active and inactive compounds in one protein family
6. Available data ChEMBL A database of bioactive and drug-like compounds http://www.ebi.ac.uk/chembl/ Kinase SARfari A chemogenomic database built around Kinase families http://www.sarfari.org/kinasesarfari/ Target proteins, Affinities with corresponding activity measures, Assays, Compounds, Pubmeds, Uniprot
7. Knowledge retrieval – Why were these technique chosen? Tool Semantic Web - Discover relations - Linking data Data Model RDF - Set of relationships - Resources (URI) Query Langugage SPARQL - Independent of RDF formats The Semantic Web - on the respective Roles of XML and RDF Stefan Decker1, Frank van Harmelen3,4, Jeen Broekstra4 Michael Erdmann5, Dieter Fensel3, Ian Horrocks 2, Michel Klein3, Sergey Melnik 1
8. Knowledge retrieval – Why Linking data? Look at other knowledge bases to Retrieve data that ChEMBL don’t contain… pathways chebi information taxonomy … Bio2RDF, Dbpedia, DrugBank, etc
12. Conclusions Semantic web contributes to the discovery of (new)relations SPARQL enables querying against ChEMBL for pharmaceutical data ChEMBL holds information about bioactive compounds Together these parts contribute to the pharmaceutical drug discovery
13. Where next? How is available pharmaceutical data from ChEMBL reached in an efficient way and in what way may this data be used? Explore additional (available) data Develop precise queries for a certain cause Go further into the usage of retrieved data
14. Where next? Develop queries Accessing from all possible ways “ Premake” queries Wizard Visualize information Biological Networking Moss Manager Other languages A visit to the Mark Wilkinson group in Vancouver