HuPSON: the human physiology simulation ontology

Journal of Biomedical Semantics

Martin Hofmann-Apitius²  Heinz-Theodor Mevissen¹  Bernard de Bono³  Bijun Zhang¹  Hui Li¹  Jiali Wang¹  Ashutosh Malhotra²  Erfan Younesi²  Michaela Gündel² 

[1] Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Schloss Birlinghoven, Sankt Augustin, Germany;Bonn-Aachen International Center for Information Technology (B-IT), University of Bonn, Bonn, Germany;University College London (UCI), Gower Street, WC1E 6BT, London, UK

关键词: Text mining;    Semantics;    Ontology;    Interoperability;    Algorithm;    Simulation;   

Others  :  806512
DOI  :  10.1186/2041-1480-4-35

 received in 2013-05-15, accepted in 2013-10-07,  发布年份 2013

【 摘 要 】

Background

Large biomedical simulation initiatives, such as the Virtual Physiological Human (VPH), are substantially dependent on controlled vocabularies to facilitate the exchange of information, of data and of models. Hindering these initiatives is a lack of a comprehensive ontology that covers the essential concepts of the simulation domain.

Results

We propose a first version of a newly constructed ontology, HuPSON, as a basis for shared semantics and interoperability of simulations, of models, of algorithms and of other resources in this domain. The ontology is based on the Basic Formal Ontology, and adheres to the MIREOT principles; the constructed ontology has been evaluated via structural features, competency questions and use case scenarios.

The ontology is freely available at: http://www.scai.fraunhofer.de/en/business-research-areas/bioinformatics/downloads.html webcite (owl files) and http://bishop.scai.fraunhofer.de/scaiview/ webcite (browser).

Conclusions

HuPSON provides a framework for a) annotating simulation experiments, b) retrieving relevant information that are required for modelling, c) enabling interoperability of algorithmic approaches used in biomedical simulation, d) comparing simulation results and e) linking knowledge-based approaches to simulation-based approaches. It is meant to foster a more rapid uptake of semantic technologies in the modelling and simulation domain, with particular focus on the VPH domain.

【 授权许可】

   
2013 Gündel et al.; licensee BioMed Central Ltd.

【 图 表 】

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【 参考文献 】

• [1]Stevens R, Goble C, Horrocks I, Bechhofer S: OILing the way to machine understandable bioinformatics resources. IEEE Trans Inf Technol Biomed 2002, 6(2):129-134.
• [2]Bodenreider O: Biomedical ontologies in action: role in knowledge management, data integration and decision support. Yearb Med Inform 2008, 47(Suppl 1):67-79.
• [3]Prior F: Medical knowledge discovery and management. Mil Med 2009, 174(5 Suppl):21-26.
• [4]IHrynaszkiewicz I: A call for BMC research notes contributions promoting best practice in data standardization, sharing and publication. BMC Res Notes 2010, 3:235. BioMed Central Full Text
• [5]Marcha M, Allard J, Duriez C, Cotin S: Towards a framework for assessing deformable models in medical simulation. In Proceedings of ISBMS. London, UK: Springer; 2008:176-184.
• [6]Whetzel P, Noy N, Shah N, Alexander P, Nyulas C, Tudorache T, Musen M: BioPortal: enhanced functionality via new Web services from the national center for biomedical ontology to access and use ontologies in software applications. Nucleic Acids Res 2011, 39:5-07.
• [7]Courtot M, Juty N, Knüpfer C, Waltemath D, Zhukova A, Dräger A, Dumontier M, Finney A, Golebiewski M, Hastings J, Hoops S, Keating S, Kell D, Kerrien S, Lawson J, Lister A, Lu J, Machne R, Mendes P, Pocock M, Rodriguez N, Villeger A, Wilkinson D, Wimalaratne S, Laibe C, Hucka M, Le Novère N: Controlled vocabularies and semantics in systems biology. Mol Syst Biol 2011, 7:543.
• [8]Silver G, Lacy L, Miller J: Ontology based representations of simulation models following the process interaction world view. In Proceedings of the 2006 winter simulation conference. Monterey, California: Winter Simulation Conference; 2006.
• [9]Miller J, Baramidze G, Fishwick P: Investigating ontologies for simulation and modelling. In Proceedings of the 37th annual simulation symposium. Washington, DC, USA: IEEE Computer Society; 2004.
• [10]Le Novère N: Model storage, exchange and integration. BMC Neurosci 2006, 7:S11. BioMed Central Full Text
• [11]Viceconti M: Living human digital library - domain ontology and metadata (presentation slides). https://www.biomedtown.org/biomed_town/LHDL/Reception/ontologies/presentation webcite
• [12]Biomed Town: LHDL ontologies. http://www.biomedtown.org/biomed_town/LHDL/Reception/ontologies webcite
• [13]de Bono B, Hoehndorf R, Wimalaratne S, Gkoutos G, Grenon P: The RICORDO approach to semantic interoperability for biomedical data and models: strategy, standards and solutions. BMC Res Notes 2011, 4:313. BioMed Central Full Text
• [14]Gennari J, Neal M, Galdzicki M, Cook D: Multiple ontologies in action: composite annotations for biosimulation models. J Biomed Inform 2011, 44(1):146-154.
• [15]Neal M, Cook D, Gennari J: An OWL knowledge base for classifying and querying collections of physiological models: a prototype human physiome. In International conference on biomedical ontology (ICBO) 2013. Toronto, Ont, CA; 2013.
• [16]Hunter P, Coveney P, de Bono B, Diaz V, Fenner J, Frangi A, Harris P, Hose R, Kohl P, Lawford P, McCormack K, Mendes M, Omholt S, Quarteroni A, Skår J, Tegner J, Thomas S, Tollis I, Tsamardinos I, van Beek J, Viceconti M: A vision and strategy for the virtual physiological human in, 2010 and beyond. Phil Trans R Soc A 2010, 2010:2595-2614.
• [17]Sandhu P: The MathML Handbook. Hingham: Charles River Media; 2002.
• [18]OBO graph view. https://code.google.com/p/obographview webcite
• [19]Motik B, Shearer R, Horrocks I: Hypertableau reasoning for description logics. J Artif Intell Res 2009, 36:165-228.
• [20]US National Library of Medicine: Fact sheet MEDLINE. http://www.nlm.nih.gov/pubs/factsheets/medline.html webcite
• [21]Hanisch D, Fundel K, Mevissen H, Zimmer R, Fluck J: ProMiner: rule-based protein and gene entity recognition. BMC Bioinforma 2005, 6:14. BioMed Central Full Text
• [22]Gattermayer T: SCAIView: annotation and visualization system for knowledge discovery. Master’s thesis. Bonn, Germany: Life Science Informatics at Bonn-Aachen International Center for Information Technology (B-IT); 2007.
• [23]Lim E, Cloherty S, Reizes J, Mason D, Salamonsen R, Karantonis D, Lovell N: A dynamic lumped parameter model of the left ventricular assisted circulation. In Conf proc IEEE Eng Med biol Soc. Piscataway, NJ, USA: IEEE; 2007.
• [24]Liu P, Gao Y, Fu X, Lu J, Zhou Y, Wei X, Li G, Ding M, Wu H, Ye W, Liu Y, Li Z: Pump models assessed by transesophageal echocardiography during cardiopulmonary resuscitation. Chin Med J (Engl) 2002, 115(3):359-363.
• [25]Frisoni G, Fox N, Jack C Jr, Scheltens P, Thompson P: The clinical use of structural MRI in alzheimer disease. Nat Rev Neurol 2010, 6:67-77.
• [26]Ivchenko O, Younesi E, Shahid M, Wolf A, Müller B, Hofmann-Apitius M: PLIO: an ontology for formal description of protein-ligand interactions. Bioinformatics 2011, 27(12):1684-1690.
• [27]Knüpfer C, Beckstein C, Dittrich P, Le Novère N: Structure, function, and behaviour of computational models in systems biology. BMC Syst Biol 2013, 7:43. BioMed Central Full Text
• [28]Protégé project. http://protege.stanford.edu/ webcite
• [29]NCBO ontology summit 2013 ontology evaluation across the ontology lifecycle. http://ontolog.cim3.net/OntologySummit/2013/ webcite
• [30]Obrst L, Ceusters W, Mani I, Ray S, Smith B: The evaluation of ontologies - toward improved semantic interoperability. Semantic Web, Part II; 2007:139-158.
• [31]Brewster C, Alani H, Dasmahapatra S, Wilks Y: Data driven ontology evaluation. Lisbon, Portugal: In Proceedings of Int. Conf. on Language Resources and Evaluation; 2004.
• [32]Hoehndorf R, Dumontier M, Gkoutos G: Evaluation of research in biomedical ontologies. Brief Bioinform 2012. http://bib.oxfordjournals.org/content/early/2012/09/07/bib.bbs053.abstract webcite
• [33]McKain D: SnuggleTeX version 1.2.2. University of Edinburgh; http://www2.ph.ed.ac.uk/snuggletex/documentation/overview-and-features.html webcite
• [34]Porter M: An algorithm for suffix stripping. Proc Natl Acad Sci U S A 1980, 14(3):130-137.
• [35]The Apache Software Foundation: Apache openNLP. http://incubator.apache.org/opennlp/ webcite
• [36]Rector A: Modularisation of domain ontologies implemented in description logics and related formalisms including OWL. In K-CAP ‘03 proceedings of the 2nd international conference on knowledge capture. New York, NY, USA: ACM Press; 2003.
• [37]National center for biomedical ontology. http://www.bioontology.org/ webcite
• [38]Courtot M, Gibson F, Lister A, Malone J, Schober D, Brinkman R, Ruttenberg A: MIREOT: The minimum information to reference an external ontology term. Appl Ontol 2011, 23-33.
• [39]The CellML project: CellML viewer. http://www.cellml.org/tools/downloads/cellml-viewer webcite
• [40]BioPortal: Phenotypic quality. http://bioportal.bioontology.org/ontologies/1107 webcite
• [41]Gene Ontology Consortium: The gene ontology in 2010: extensions and refinements. Nucleic Acids Res 2010, 38:1-5.
• [42]de Matos P, Alcántara R, Dekker A, Ennis M, Hastings J, Haug K, Spiteri I, Turner S, Steinbeck C: Chemical entities of biological interest: an update. Nucleic Acids Res 2010, 38:49-54.
• [43]Osborne J, Flatow J, Holko M, Lin S, Kibbe W, Zhu L, Danila M, Feng G, Chisholm R: Annotating the human genome with disease ontology. BMC Genomics 2009, S1:S6.
• [44]Meehan T, Masci A, Abdulla A, Cowell L, Blake J, Mungall C, Diehl A: Logical development of the cell ontology. BMC Bioinforma 2011, 12:6. BioMed Central Full Text
• [45]Golbreich C, Zhang S, Bodenreider O: The foundational model of anatomy in OWL: experience and perspectives. Web Semant 2006, 4(3):181-195.
• [46]Grenon P, Smith B: SNAP and SPAN: Towards dynamic spatial ontology. Spat Cogn Comput 2004, 4:69-103.
• [47]Borgo S, Masolo C: Ontological Foundations of DOLCE. In Handbook on ontologies. Second edition. Berlin Heidelberg, Germany: Springer Verlag; 2009:361-382.
• [48]IEEE: Suggested upper merged ontology. http://www.ontologyportal.org/ webcite
• [49]Herre H, Heller B, Burek P, Hoehndorf R, Loebe F, Michalek H: General formal ontology (GFO): a foundational ontology integrating objects and processes. Part I: basic principles. University of Leipzig, Leipzig: Research Group Ontologies in Medicine (Onto-Med); 2010.
• [50]Cycorp: Overview of OpenCyc. http://cyc.com/cyc/opencyc/overview webcite
• [51]Smith B, Ashburner M, Rosse C, Bard J, Bug W, Ceuster W, Goldberg L, Eilbeck K, Ireland A, Mungall C, Leontis N, Rocca-Serra P, Ruttenberg A, Sansone S, Scheuermann R, Shah N, Whetzel P, Lewis S, The OBI Consortium: The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nat Biotechnol 2007, 25:1251-1255.
• [52]W3C: RDF vocabulary description language 1.0: RDFSchema. http://www.w3.org/TR/rdf-schema/ webcite
• [53]Dublin Core Metadata Initiative: Making it easier to find information. http://dublincore.org/ webcite
• [54]Smith B, Ceusters W, Klagges B, Köhler J, Kumar A, Lomax J, Mungall C, Neuhaus F, Rector A, Rosse C: Relations in biomedical ontologies. Genome Biol 2005, 6(5):R46. BioMed Central Full Text