Systems Biology Model Semantics and Integration
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This document discusses the integration of biological data using rule-based mediation (rbm) to resolve syntactic and semantic heterogeneity across various data sources, forming a core ontology for better reasoning and querying. It emphasizes the adaptability of ontologies in the context of systems biology, noting the approach of avoiding ontology merging and instead creating multiple core ontologies. The presentation also highlights ongoing projects and applications that utilize the rbm framework for model annotation and data integration.
Systems Biology Model Semantics and Integration
- 1. Systems Biology Model Semantics and Integration Allyson Lister Biology, Neurosciences & Computing Group Newcastle University 29 July 2011 This presentation is licensed under Creative Commons BY-SA 2.5
- 2. Background in Standards In the beginning, there was syntax ... TrEMBL, FuGE, SBML ...then came content ... MIGS/MIMS ...And ultimately, semantics OBI, SBO, BioPAX
- 3. Background in Integration Throughout, an interest in data integration Redundancy removal in TrEMBL
- 4. International Protein Index (IPI)
- 5. FuGE-based metadata database and data storage (SyMBA)
- 7. Rule-Based Mediation (RBM) Integrate data from multiple data sources into a single, core ontology for reasoning, querying and data extraction back to a chosen (non-OWL) format
- 8. RBM (continued) Resolution of syntactic and semantic heterogeneity occurs separately The core ontology is a semantically-rich description of the research domain of interest
- 9. Syntactic ontologies pass data to the core via SWRL Are either syntactic translations of data formats into OWL or pre-existing OWL ontologies Mainly uses existing, independent ontologies and off-the-shelf libraries and applications
- 10. RBM (continued) Is not Ontology alignment Alignment often a prelude to ontology merging, and used where domains at least partly intersect
- 11. We do not intend to merge ontologies, and each data source may be very different from another Format reconciliation We are not trying to create a single, overarching format – just quickly pull data from many formats
- 12. Systems Biology and RBM Add information to models Add new interactions/pathways to existing models
- 13. Add new biological annotation to existing models
- 14. Build skeleton models of requested interactions/pathways
- 15. RBM Overview UniprotKB CellML PathwayCommons XML XML OWL OWL BioPAX Core Ontology Instances Resolve syntactic heterogeneity Resolve semantic heterogeneity, reasoning, querying Retrieve data MFO Export to SBML, other formats If required BioModels XML MFO ... XML OWL
- 16. Why have an OWL intermediary where converters exist? BioPAX ↔ SBML, CellML ↔ SBML converters exist Lossy (due to different scopes of each format)
- 17. Might not get what we need from such conversion
- 18. Why have an OWL intermediary where converters exist? BioPAX ↔ SBML, CellML ↔ SBML converters exist With SWRL rules we can pull information for exactly those portions of each format we're interested in
- 19. Not dependent upon external developers if the meaning or structure of a format changes
- 20. Easier to change rules (especially for web applications or novices) and re-run mappings than re-write hard-coded Java/perl etc.
- 21. The core ontology Ideally, a core ontology should be a tightly-scoped ontology describing the domain of interest
- 22. Multiple core ontologies can be created as necessary to address multiple biological questions
- 23. We began with an ontology describing the basics of telomere uncapping
- 24. Sharing common concepts among core ontologies To make it easier to swap out core ontologies, use a common ontology which all can inherit BioPAX Level 3 (and perhaps the SBPAX3 extension) is being considered for my research
- 25. Such an ontology can be selectively enriched with the biological information of interest
- 26. Only a small number of domain-specific SWRL rules would be needed with each new core ontology
- 27. Visible face of RBM Saint pulls suggested MIRIAM annotation and possible interactors from web services
- 28. “syntactic” integration of data, or direct querying of WSs based on query strings built from the SBML/CellML models
- 29. “semantic” Saint will also pull information out of RBM-integrated data
- 30. Reasoning Not much reasoning over BioPAX yet, though as a component of my core ontology this will be coming soon
- 31. Reasoning over MFO models is quick, which is to be expected given the (deliberate) relative lack of complexity
- 32. Reasoning Reasoning and querying over the core ontology has already discovered new annotations as well as possible identification of unknown species in SBML models
- 33. Reasoning tends to be slower than I'd like, although much of it can be done behind the scenes and the results stored for later queries (i.e. with SQWRL)
- 34. Many interesting projects Model annotation for Synthetic Biology Goksel Misirli and others BioPAX ↔ SBML SBPAX3 and other work by Oliver Ruebenacker and others
- 35. EBI BioPAX ↔ SBML conversion
- 36. RBM using both as data sources
- 37. Many interesting projects SBML and OWL MFO
- 38. SBMLHarvester by Robert Hoehndorf and others CellML and OWL
- 39. Related Work from Us Model annotation for synthetic biology: http://dx.doi.org/10.1093/bioinformatics/btr048
- 40. Rule-Based Mediation http://cisban-silico.cs.ncl.ac.uk/RBM/http://dx.doi.org/10.1186/2041-1480-1-S1-S3
- 41. MFO: http://cisban-silico.cs.ncl.ac.uk/MFO/ doi:10.2390/biecoll-jib-2007-80
- 42. Related Work from Us SyMBA: http://symba.sf.net
- 43. Saint: http://saint-annotate.sf.net http://dx.doi.org/10.1093/bioinformatics/btp523
- 44. Other Related Work SBPAX3 http://sourceforge.net/apps/mediawiki/biopax/index.php?title=SBPAX3
- 46. SBML -> BioPAX conversion sbml2biopax http://www.ebi.ac.uk/compneur-srv/sbml/converters/SBMLtoBioPax.html
- 47. CellML and OWL, Wimalaratne et al. doi: 10.1093/bioinformatics/btp391
- 48. Thank you! And thanks also to Phil Lord and Neil Wipat, my PhD supervisors
- 49. Biology, Neurosciences & Computing Group at the Computing Science Department, Newcastle University
- 50. CISBAN
- 51. BBSRC
- 52. Contact Me Contact me @allysonlister