Annotation of SBML Models Through Rule-Based Semantic Integration

Bio-Ontologies SIG, ISMB 200928 June 2009

Allyson Lister, Phillip Lord, Matthew Pocock, Anil WipatCISBAN and Newcastle University

http://www.cisban.ac.uk/RBM helpdesk@cisban.ac.uk

Presentation slides covered under the CC-BY-SA 2.5

Telomeres and Ageing

Image: Public Domain, NASA, from http://commons.wikimedia.org/wiki/File:Telomere_caps.gif

Checkpoint response to telomere uncapping in budding yeast

Proctor et al. [1]

Image and Model: [1]

What is SBML?

Standard formatWidely used (100+ tools)Represents the mathematical modelEnables linking to the underlying biology

Model Annotation Life Cycle

Get dataRead literature

(Re)build modelParameterise

Run and test model

Examine results

Challenges in Model Annotation

Knowledge in lots of places Hard for a single modeller to retrieve all

available knowledge Most existing data integration tools are not

suitable for modellers’ needs Many integration methods are purely syntactic

Rule-Based Mediation

A core ontology, which is a semantically-rich description of the research domain of interest

A set of source ontologies, which are syntactic translations of data formats into OWL

Resolution of syntactic and semantic heterogeneity occurs separately

Can use existing, independent ontologies

Where is the knowledge?

Data Source Number of Rules

BioGRID 17

Pathway Commons 11

UniProtKB 11

Input data sources: UniProtKB, BioGRID, Pathway CommonsData can end up in SBML format via MFO [2]

How are the data sources integrated?

UniprotKB

BioGRID

PathwayCommons

XML

XML

OWL

OWL

OWLTelomereOntology

Instances

Resolvesyntactic

heterogeneity

Resolvesemantic

heterogeneity

Reviews of integration types [3-6] Reviews for ontology mapping [7-11]

Retrievedata

MFO

Exportto

SBML

Achieving the XML to OWL Conversion

The XMLTab plugin for Protégé quickly creates classes and instances from XML

Provides syntactic transformation of data But, not multiple XML files May not be in active development

Syntactic Ontologies →Telomere Ontology

Rules written in SWRL Queries over the telomere ontology are written

in SQWRL SWRLTab and Jess are used to run these rules

and queries While writing rules/queries is mainly manual,

running them is automatic Semantic value is added to the information by

mapping it to a semantically-rich core ontology

Mappings from UniProtKB

upkb:Text(?l, ?value) ˄

upkb:locationSlot(?s, ?l) ˄

swrlb:equal(?value, “Nucleus”) →

tuo:Nucleus(?l)

What is RAD9?

Tell me about something called ‘rad9’ Results could be added back to the existing

model Cross-references SBO annotations Compartment localisations Recommended name

These results allow the addition of information required by the MIRIAM guidelines

What interacts with RAD9?

In Proctor et al., there are four interacting partners with RAD9Two were identified within the model, and were found by querying the telomere ontologyOf the unknown partners, one was provisionally identified as MEC1.

Summary

SBML models require large amounts of data to be mathematically and biologically complete

A two-step integration “rule-based mediation” helps model annotation

Off-the-shelf technology was used Eases the task of fulfilling MIRIAM guidelines SWRL rules were used to populate our semantically-rich

telomere ontology SQWRL was used for querying We found new knowledge that the modeller was not

aware of

Phillip Lord, Matthew Pocock, Anil Wipat

Carole Proctor (10.1098/rsif.2006.0148)

Tom Kirkwood

Reviewers and conference organisers

Funding for CISBAN provided by BBSRC/EPSRC grant ref BB/C008200/1

http://www.cisban.ac.uk/RBM

Thank you!

Funding for CISBAN provided by BBSRC/EPSRC grant ref BB/C008200/1

xkcd.com

References

1. CJ Proctor, DA Lydall, RJ Boys, et al. Modelling the checkpoint response to telomere uncapping in budding yeast. Journal of The Royal Society Interface, Vol. 4, No. 12. (22 February 2007), pp. 73-90.

2. AL Lister, M Pocock, A Wipat, Integration of constraints documented in SBML, SBO, and the SBML Manual facilitates validation of biological models. Journal of Integrative Bioinformatics, Vol. 4, No. 3. (2007), 80.

3. Stephan Philippi and Jacob Kohler. Addressing the problems with life-science databases for traditional uses and systems biology. Nature Reviews Genetics, 7(6):482–488, May 2006

4. W. Sujansky. Heterogeneous database integration in biomedicine. J Biomed Inform, 34(4):285–298, August 2001.

5. Lincoln D Stein. Integrating biological databases. Nat Rev Genet, 4(5):337–345, May 2003.

6. R. Alonso-Calvo et al. An agent- and ontology-based system for integrating public gene, protein, and disease databases. J Biomed Inform, 40(1):17–29, February 2007.

References

7. Marie C. Rousset and Chantal Reynaud. Knowledge representation for information integration. Inf. Syst., 29(1):3–22, 2004.

8. Li Xu and David W. Embley. Combining the Best of Global-as-View and Local-as-View for Data Integration. In Anatoly E. Doroshenko, Terry A. Halpin, Stephen W. Liddle, Heinrich C. Mayr, Anatoly E. Doroshenko, Terry A. Halpin, Stephen W. Liddle, and Heinrich C. Mayr, editors, ISTA, volume 48 of LNI, pages 123–136. GI, 2004.

9. Natalya F. Noy and Mark A. Musen. The PROMPT suite: interactive tools for ontology merging and mapping. Int. J. Hum.-Comput. Stud., 59(6):983–1024, December 2003.

10. Holger Wache et al. Ontology-based integration of information — a survey of existing approaches. In H. Stuckenschmidt, editor, Proceedings of the IJCAI’01 Workshop on Ontologies and Information Sharing, Seattle, Washington, USA, Aug 4-5, pages 108–117, 2001.

11. Jinguang Gu, Baowen Xu, and Xinmeng Chen. An XML query rewriting mechanism with multiple ontologies integration based on complex semantic mapping. Information Fusion, 9(4):512–522, October 2008.

Small Print

This presentation is covered under the CC-BY-SA 2.5 (http://creativecommons.org/licenses/by-sa/2.5/ ) license and can be found on slideshare at: http://www.slideshare.net/allysonlister/annotation-of-sbml-models-through-rulebased-semantic-integration

The ontologies created by the authors are covered under the CC-BY 3.0 license, and external ontologies are governed under their own licensing requirements (specifically, SBO, which is covered under the Artistic License as defined on its SourceForge project site at http://sourceforge.net/projects/sbo/).

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