An ontological modeling approach to cerebrovascular disease studies: The NEUROWEB case

Journal of Biomedical Informatics

Volumn 43, Issue 4, 2010, Pages 469-484

  Colombo, Gianluca ^e   Merico, Daniele ^a   Boncoraglio, Giorgio ^f   De Paoli, Flavio ^e   Ellul, John ^b   Frisoni, Giuseppe ^e   Nagy, Zoltan ^d   van der Lugt, Aad ^g   Vassányi, István ^c   Antoniotti, Marco ^e  

^a UNIVERSITY OF TORONTO   (Canada)

^b UNIVERSITY OF PATRAS   (Greece)

^c UNIVERSITY OF PANNONIA   (Hungary)

^d SEMMELWEIS UNIVERSITY   (Hungary)

^e UNIVERSITY OF MILANO BICOCCA   (Italy)

^f DEPARTMENT OF NEUROSURGERY   (Italy)

^g ERASMUS MEDICAL CENTER   (Netherlands)

Author keywords

Association studies; Biomedical ontologies; Clinical phenotypes; Data integration

Indexed keywords

BIOMEDICAL ONTOLOGIES; CDS; CEREBROVASCULAR DISEASE; CEREBROVASCULAR DISORDERS; CLINICAL DATA; DATA INTEGRATION; DATA SETS; EUROPEAN UNION; INTEGRATION PROBLEMS; MEDICAL CONCEPTS; MODELING APPROACH; ONTOLOGICAL MODELS; SPECIFIC PROTOCOL; STATISTICAL CORRELATION; STATISTICAL ROBUSTNESS; THREE-LAYER;

DATA HANDLING; DATA STORAGE EQUIPMENT; DIAGNOSIS;

ONTOLOGY;

ARTICLE; ATHEROSCLEROTIC CARDIOVASCULAR DISEASE; ATHEROSCLEROTIC PLAQUE; BRAIN DAMAGE; BRAIN ISCHEMIA; CEREBROVASCULAR DISEASE; CLINICAL INDICATOR; COMPUTER ASSISTED TOMOGRAPHY; DATA ANALYSIS; DATA BASE; DIAGNOSTIC VALUE; DIGITAL SUBTRACTION ANGIOGRAPHY; DISEASE CLASSIFICATION; DISEASE MODEL; ELECTROCARDIOGRAM; GENOTYPE PHENOTYPE CORRELATION; INFORMATION RETRIEVAL; NEUROWEB; NUCLEAR MAGNETIC RESONANCE; PATIENT CODING; PHENOTYPE; PRIORITY JOURNAL; STATISTICS; STROKE; TAXONOMY; TRANSESOPHAGEAL ECHOCARDIOGRAPHY; CEREBROVASCULAR DISORDERS; CLASSIFICATION; FACTUAL DATABASE; GENETICS; GENOTYPE; HUMAN; INTERNET; THEORETICAL MODEL;

CEREBROVASCULAR DISORDERS; DATABASES, FACTUAL; GENOTYPE; HUMANS; INTERNET; MODELS, THEORETICAL; PHENOTYPE;

EID: 77954142976     PISSN: 15320464     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jbi.2009.12.005     Document Type: Article

References (71)

1. Botstein D., Risch N.J. Discovering genotypes underlying human phenotypes: past successes for mendelian disease, future approaches for complex disease. Nat Genet 2003, 33(Suppl.):228-237.
2. Tabor H.K., Risch N.J., Myers R.M. Candidate-gene approaches for studying genetic traits: practical considerations. Nat Rev Genet 2002, 3(5):391-397.
3. Beneventano D., Bergamaschi S., Guerra F., Vincini M. Synthesizing an integrated ontology. IEEE Internet Comput 2003, 7(5):42-51.
4. Beneventano D., Bergamaschi S., Lodi S., Sartori C. Consistency checking in complex object database schemata with integrity constraints. IEEE Trans Knowledge Data Eng 1998, 10(4):576-598.
5. Lenz R., Beyer M., Kuhn K.A. Semantic integration in healthcare networks. Int J Med Inform 2006, 76(2-3):201-207.
6. Brazhnik O., Jones J.F. Anatomy of data integration. J Biomed Inform 2007, 40(3):252-269.
7. Rahm E., Bernstein P.A. A survey of approaches to automatica schema matching. VLDB J 2001, 10(4):334-350.
8. Pérez-Rey D., Maojo V., Garcia-Remesal M., Alonso-Calvo R., Billhardt H., Martin-Sánchez F., et al. ONTOFUSION: ontology-based integration of genomic and clinical databases. Comput Biol Med 2006, 36(7):712-730.
9. Sun Y. Methods for automated concept mapping between medical databases. J Biomed Inform 2004, 37(3):162-178.
10. Alladin-eHealth Project. Document at 2007. http://www.alladin-ehealth.org/Pub/Docs/D9.1.pdf.
11. Arens Y., Hsu C.-N., Knoblock C.A. Query processing in the SIMS information mediator. Readings in agents 1998, 82-90. Morgan Kaufmann Publishers Inc.
12. Sun J., Miao H., Cao X. A domain formal ontology and the application in service component retrieval. Proceedings of the international conference on software engineering advances (ICSEA), Tahiti, French Polynesia 2006, IEEE Computer Society.
13. Garcia-Remesal M., Maojo V., Billhardt H., Crespo J., Alonso-Calvo R., Perez-Rey D., et al. ARMEDA II: supporting genomic medicine through the integration of medical and genetic databases. Proceedings of the fourth IEEE symposium on bioinformatics and bioengineering (BIBE'04) 2004, IEEE Computer Society.
14. Köhler J., Philippi S., Lange M. Semeda: ontology based semantic integration of biological databases. Bioinformatics 2003, 19(18):2420-2427.
15. Mougin F., Burgun A., Bodenreider O., Chabalier J., Loréal O., Beux P. Automatic methods for integrating biomedical data sources in a mediator-based system. DILS '08: Proceedings of the fifth international workshop on data integration in the life sciences 2008, 61-76. Springer-Verlag, Heidelberg, Berlin.
16. Sahoo S.S., Bodenreider O., Rutter J.L., Skinner K.J., Sheth A.P. An ontology-driven semantic mashup of gene and biological pathway information: application to the domain of nicotine dependence. J Biomed Inform 2008, 41(5):752-765.
17. Pérez-Rey D., Maojo V., García-Remesal M., Alonso-Calvo R., Billhardt H., Martin-Sánchez F., et al. ONTOFUSION: ontology-based integration of genomic and clinical databases. Comput Biol Med 2005.
18. Coulet A., Smaïl-Tabbone M., Benlian P., Napoli A., Devignes M.-D. Ontology-guided data preparation for discovering genotype-phenotype relationships. BMC Bioinform 2008, 9(S-4).
19. Rubin D.L., Lewis S.E., Mungall C.J., Misra S., Westerfield M., Ashburner M., et al. National Center for Biomedical Ontology: advancing biomedicine through structured organization of scientific knowledge. OMICS 2006, 10(2):185-198.
20. Coulet A, Smaïl-Tabbone M, Benlian P, Napoli A, Devignes M-D. SNP-converter: an ontology-based solution to reconcile heterogeneous SNP descriptions for pharmacogenomic studies. In: DILS; 2006. p. 82-93.
21. Burgun A., Bodenreider O. Accessing and integrating data and knowledge for biomedical research. Yearbook Med Inform 2008, 91-101.
22. So H.-C., Chen R.Y.L., Chen E.Y.H., Cheung E.F.C., Li T., Sham P.C. An association study of rgs4 polymorphisms with clinical phenotypes of schizophrenia in a chinese population. Am J Med Genet Part B, Neuropsychiatr Genet 2008, 147B(1):77-85.
23. Lee C., Kong M. An interactive association of common sequence variants in the neuropeptide y gene with susceptibility to ischemic stroke. Stroke 2007, 38(10):2663-2669.
24. Boncoraglio G.B., Bodini A., Brambilla C., Carriero M.R., Ciusani E., Parati E.A. An effect of the pai-1 4g/5g polymorphism on cholesterol levels may explain conflicting associations with myocardial infarction and stroke. Cerebrovasc Dis 2006, 22(2-3):191-195.
25. Scheuermann RH, Ceuster W, Smith B. Towards an ontological treatment of disease and diagnosis, cf. March 2009, in press. http://summit2009.amia.org/.
26. Formal ontology in conceptual analysis and knowledge representation 1994, Kluwer Academic Press. N. Guarino, R. Poli (Eds.).
27. Bouquet P., Donà A., Serafini L., Zanobini S. ConTeXtualized local ontology specification via CTXML. MeaN-02 - AAAI workshop on meaning negotiation, Edmonton, Alberta, Canada 2002, AAAI.
28. Van der Pet P.E., Mars N.J.I. Bottom-up construction of ontologies. IEEE Trans Knowledge Data Eng 1998, 10(4):513-526.
29. Bard J.B., Rhee L., Seung Y. Ontology in biology: design, application and future challenges. Nat Rev Genet 2004, 3:213-222.
30. Fielding JM, Simon J, Ceusters W, Smith B. Ontological theory for ontological engineering: biomedical systems information integration. In: Proceedings of the ninth international conference on the principles of knowledge representation and reasoning (KR2004), Whistler, BC, Canada; June 2004.
31. Gomez-Perez A., Corcho O., Fernandez-Lopez M. Ontological engineering 2004, Springer-Verlag, New York, NY, USA.
32. Scheuermann R, Smith B. Signs, symptoms and findings: first steps toward an ontology of clinical phenotypes. Web site at Dallas Phenotype Workshop; September 2008. http://www.bioontology.org/wiki/index.php/DallasWorkshop.
33. Smith C., Goldsmith C.A., Eppig J. The mammalian phenotype ontology as a tool for annotating, analyzing and comparing phenotypic information. Genome Biol 2004, 6(1):R7.
34. PATO - Phenotypic Quality Ontology. Web site at http://www.bioontology.org/wiki/index.php/PATO:MainPage.
35. Bodenreider O., Smith B., Kumar A., Burgun A. Investigating subsumption in SNOMED-CT: an exploration into large description logic-based biomedical terminologies. Artif Intell Med 2007, 39(3):183-195.
36. Linksvan der Kooij J., Goossen W.T., Goossen-Baremans A.T., de Jong-Fintelman M., van Beek L. Using SNOMED-CT codes for coding information in electronic health records for stroke patients. Stud Health Technol Inform 2006, 124:815-823.
37. Cimino J.J. Coding systems in health care. Methods Inform Med 1996, 35(4-5):273-284. [Review paper].
38. Disease Ontology (DisO) - The NUgene Project. Web site at http://diseaseontology.sf.net.
39. Adams H.P., Bendixen B.H., Kappelle J.J., Biller J., Love B.B., Gordon D.L., et al. Classification of subtype of acute ischemic stroke, definition for use in a multicenter clinical trial, TOAST. Trial of Org 10172 in Acute Stroke Treatment. Stroke 1993, 24:35-41.
40. Goldstein L.B., Jones M.R., Matchar D.B., Edwards L.J., Hoff J., Chilukuri V., et al. Improving the reliability of stroke subgroup classification using the Trial of ORG 10172 in Acute Stroke Treatment (toast) criteria. Stroke 2001, 32:1091-1097.
41. Ay H., Furie K.L., Singhal A., Smith W.S., Sorensen A.G., Koroshetz W.J. An evidence-based causative classification system for Acute Ischemic Stroke. Ann Neurol 2005, 58:688-697.
42. Taylor C.F., Field D., Sansone S.-A., Aerts J., Apweiler R., Ashburner M., et al. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 2008, 26(8):889-896.
43. Donnelly K. SNOMED-CT: the advanced terminology and coding system for eHealth. Stud Health Technol Inform 2006, 121:279-290.
44. Lipscomb C.E. Medical Subject Headings (MeSH). Bull Med Library Assoc 2000, 88(3).
45. Stenson P.D., Ball E.V., Mort M., Phillips A.D., Shiel J.A., Thomas N.S., et al. Human Gene Mutation Database (HGMD): 2003 update. Human Mutat 2003, 21(6):577-581.
46. Stenson P.D., Ball E., Howells K., Phillips A., Mort M., Cooper D.N. Human Gene Mutation Database: towards a comprehensive central mutation database. J Med Genet 2008, 45(2):24-126.
47. Lewis S.E. Gene Ontology: looking backwards and forward. Genome Biol 2004, 6(103).
48. Spasic I., Ananiadu S., McNaught J., Kumar A. Text mining and ontologies in biomedicine: making sense of raw text. Brief Bioinform 2005, 6(3):239-251.
49. Chen Y., Perl Y., Geller J., Cimino J.J. Analysis of a study of the users, uses, and future agenda of the UMLS. J Maerican Med Inform Assoc 2007, 14(2):221-231.
50. ICD9-CM. Web site at http://www.icd9cm.net.
51. ICD10. Web site at http://www.who.int/classifications/icd.
52. WordNet: an electronic lexical database 1998, MIT Press. C. Fellbaum (Ed.).
53. Jensen C.S., Snograss R.T. Temporal data management. Knowledge Data Eng 1999, 11(1):36-44.
54. Artale A, Parent C, Spaccapietra S. Modeling the evolution of objects in temporal information systems. In: Kirchberg M, Hegner SJ, editors, Proceedings of the fourth international symposium of foundations of information and knowledge-based systems. Lecture notes in computer science, vol. 3861; 2006. p. 22-42.
55. Shahar Y. Timing is everything: temporal reasoning and temporal data maintenance in medicine. In: Joint European conference on artificial intelligence in medicine and medical decision making (AIMDM'99). Lecture notes in artificial intelligence, vol. 1620; 1999. p. 30-46.
56. Rector A.L., Rogers J. Ontological and practical issues in using a description logic to represent medical concept systems: experiences from GALEN. Lecture notes in computer science 2006, vol. 4126:197-231. Springer-Verlag.
57. Palma P, Llamas B, Gonzales A, Menarguez M. Acquisition and representation of causal and temporal knowledge in medical domains. In: Knowledge-based intelligent information and engineering systems, seventh international conference, KES 2003, Lecture notes in computer science, vol. 2777; 2003. p. 1284-90.
58. International HapMap Consortium. A haplotype map of the human genome. Nature 2005, 437(7063):1299-1320.
59. Sherry S.T., Ward M.H., Kholodov M., Baker J., Phan L., Smigielski E.M., et al. dbSNP: the NCBI database of genetic variation. Nucleic Acids Res 2001, 29:308-311.
60. Meschia J.F. Clinically translated ischemic stroke genomics. Stroke 2004, 35(11 Suppl. 1):2735-2739.
61. Kaneisha M., Goto S. KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acid Res 2000, 28:27-30.
62. Kaneisha M., Goto S., Hattori M., Aoki-Kinoshita K.F., Itoh M., Kawashima M., et al. From genomics to chemical genomics: new developments in KEGG. Nucleic Acid Res 2006, 34:D354-D357.
63. Kaneisha M., Araki M., Goto S., Hattori M., Hirakawa M., Itoh M., et al. KEGG for linking genomes to life and the environment. Nucleic Acid Res 2008, 36:D480-D484.
64. Becker K., Barnes K.C., Bright T.J., Wang S.A. The genetic association database. Nat Genet 2004, 36(5):431-432.
65. The description logic handbook: theory, implementation and application 2003, Cambridge University Press, New York, NY, USA. F. Baader, D. Calvanese, D.L. McGuinness, D. Nardi, P.F. Patel-Schneider (Eds.).
66. Sattler U. Description logics for the representation of aggregate objects. Proceedings of the 14th European conference on artificial intelligence 2000, IOS Press, Amsterdam, Holland.
67. Horrocks I, Sattler U, Tobies S. Practical reasoning for expressive description logics. In: Proceedings of the sixth international conference on logic and automated programming (LPAR99), Tblisi, Georgia, 1999.
68. W3C. OWL Web Ontology Language. Web site at <>, February 2004. http://www.w3c.org/TR/owl-guide.
69. Jena - A Semantic Web Framework for Java. Web site at http://jena.sourceforge.net.
70. GlassFish. Web site at http://glassfish.dev.java.net.
71. Douglas K, Douglas S. PostgreSQL. Sams, 2nd ed.; 2005.