Similarity-based search of model organism, disease and drug effect phenotypes

Journal of Biomedical Semantics

Volumn 6, Issue 1, 2015, Pages

  Hoehndorf, Robert ^a   Gruenberger, Michael ^b   Gkoutos, Georgios V ^c   Schofield, Paul N ^b  

^a KING ABDULLAH UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Saudi Arabia)

^b ABERYSTWYTH UNIVERSITY   (United Kingdom)

^c UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

Ontology; Phenotype; Semantic similarity

Indexed keywords

EID: 84938768477     PISSN: None     EISSN: 20411480     Source Type: Journal    
DOI: 10.1186/s13326-015-0001-9     Document Type: Article

References (37)

1. Schofield PN, Hoehndorf R, Gkoutos GV. Mouse genetic and phenotypic resources for human genetics. Hum Mutat. 2012; 33(5):826-36.
2. Gkoutos GV, Schofield PN, Hoehndorf R. Computational tools for comparative phenomics: the role and promise of ontologies. Mamm Genome. 2012; 23(9-10):669-79.
3. Pesquita C, Faria D, Falcao AO, Lord P, Couto FM. Semantic similarity in biomedical ontologies. PLoS Comput Biol. 2009; 5(7):1000443. doi:10.1371/journal.pcbi.1000443.
4. Hoehndorf R, Hardy NW, Osumi-Sutherland D, Tweedie S, Schofield PN, Gkoutos GV. Systematic analysis of experimental phenotype data reveals gene functions. PLoS ONE. 2013; 8(4):60847. doi:10.1371/journal.pone.0060847.
5. Hoehndorf R, Schofield PN, Gkoutos GV. Phenomenet: a whole-phenome approach to disease gene discovery. Nucleic Acids Res. 2011; 39(18):119. doi:10.1093/nar/gkr538.
6. Hoehndorf R, Schofield PN, Gkoutos GV. An integrative, translational approach to understanding rare and orphan genetically based diseases. Interface Focus. 2013; 3(2):20120055. doi:10.1098/rsfs.2012.0055.
7. Chen Cc-K, Mungall CcJ, Gkoutos GcV, Doelken ScC, Köhler S, Ruef BcJ, et al. Mousefinder: Candidate disease genes from mouse phenotype data. Hum Mutation. 2012; 33:858-66. doi:10.1002/humu.22051.
8. Zemojtel T, Köhler S, Mackenroth L, Jäger M, Hecht J, Krawitz P, et al. Effective diagnosis of genetic disease by computational phenotype analysis of the disease-associated genome. Sci Transl Med. 2014; 6(252):252-123. doi:10.1126/scitranslmed.3009262.
9. Hoehndorf R, Hiebert T, Hardy NW, Schofield PN, Gkoutos GV, Dumontier M. Mouse model phenotypes provide information about human drug targets. Bioinformatics. 2014; 30(5):719-25. doi:10.1093/bioinformatics/btt613.
10. Dwinell MR, Worthey EA, Shimoyama M, Bakir-Gungor B, DePons J, Laulederkind S, et al. The rat genome database 2009: variation, ontologies and pathways. Nucleic Acids Res. 2009; 37(Database issue):744-49. doi:10.1093/nar/gkn842.
11. Gaudet P, Fey P, Basu S, Bushmanova YA, Dodson R, Sheppard KA, et al. dictybase update 2011: web 2.0 functionality and the initial steps towards a genome portal for the amoebozoa. Nucleic Acids Res. 2011; 39(Database-Issue):620-4.
12. Robinson PN, Köhler S, Bauer S, Seelow D, Horn D, Mundlos S. The human phenotype ontology: a tool for annotating and analyzing human hereditary disease. Am J Hum Genet. 2008; 83(5):610-5. doi:10.1016/j.ajhg.2008.09.017.
13. Smith CL, Eppig JT. The mammalian phenotype ontology as a unifying standard for experimental and high-throughput phenotyping data. Mamm Genome. 2012; 23(9-10):653-68.
14. Mungall C, Gkoutos G, Smith C, Haendel M, Lewis S, Ashburner M. Integrating phenotype ontologies across multiple species. Genome Biol. 2010; 11(1):2. doi:10.1186/gb-2010-11-1-r2.
15. Mungall C, Torniai C, Gkoutos G, Lewis S, Haendel M. Uberon, an integrative multi-species anatomy ontology. Genome Biol. 2012; 13(1):5. doi:10.1186/gb-2012-13-1-r5.
16. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry MJ, et al. Gene ontology: tool for the unification of biology. Nat Genet. 2000; 25(1):25-29. doi:10.1038/75556.
17. Gkoutos GV, Green EC, Mallon A-MM, Hancock JM, Davidson D. Using ontologies to describe mouse phenotypes. Genome Biol. 2005; 6(1):5. doi:10.1186/gb-2004-6-1-r8.
18. Hayamizu TF, Mangan M, Corradi JP, Kadin JA, Ringwald M. The adult mouse anatomical dictionary: a tool for annotating and integrating data. Genome Biol. 2005; 6(3):R29.
19. Rosse C, Mejino JLV. A reference ontology for biomedical informatics: the Foundational Model of Anatomy. J Biomed Inform. 2003; 36(6):478-500. doi:10.1016/j.jbi.2003.11.007.
20. Hoehndorf R, Oellrich A, Rebholz-Schuhmann D. Interoperability between phenotype and anatomy ontologies. Bioinformatics. 2010; 26(24):3112-8.
21. Horridge M, Bechhofer S, Noppens O. Igniting the OWL 1.1 touch paper: The OWL API. In: Proceedings of OWLED 2007: third international workshop on OWL experiences and directions.Aachen, Germany: CEUR-WS.org: 2007.
22. Kazakov Y, Krötzsch M, Simancik F. The incredible elk. J Automated Reasoning. 2014; 53(1):1-61. doi:10.1007/s10817-013-9296-3.
23. Pesquita C, Faria D, Bastos H, Ferreira A, Falcao A, Couto F. Metrics for GO based protein semantic similarity: a systematic evaluation. BMC Bioinformatics. 2008; 9(Suppl 5):4. doi:10.1186/1471-2105-9-S5-S4.
24. Oellrich A, Hoehndorf R, Gkoutos GV, Rebholz-Schuhmann D. Improving disease gene prioritization by comparing the semantic similarity of phenotypes in mice with those of human diseases. PLoS ONE. 2012; 7(6):38937. doi:10.1371/journal.pone.0038937.
25. Bello SM, Richardson JE, Davis AP, Wiegers TC, Mattingly CJ, Dolan ME, et al. Disease model curation improvements at mouse genome informatics. Database. 2012; 2012:063. doi:10.1093/database/bar063.
26. Harris TW, Antoshechkin I, Bieri T, Blasiar D, Chan J, Chen WJ, et al. WormBase: a comprehensive resource for nematode research. Nucleic Acids Res. 2010; 38(suppl 1):463-7. doi:10.1093/nar/gkp952.
27. Cherry JM, Adler C, Ball C, Chervitz SA, Dwight SS, Hester ET, et al. SGD: Saccharomyces genome database. Nucleic Acids Res. 1998; 26(1):73-9. doi:10.1093/nar/26.1.73.
28. Amberger J, Bocchini C, Hamosh A. A new face and new challenges for Online Mendelian Inheritance in Man (OMIM). Hum Mutat. 2011; 32:564-7.
29. Weinreich SS, Mangon R, Sikkens JJ, Teeuw ME, Cornel MC. Orphanet: a european database for rare diseases. Ned Tijdschr Geneeskd. 2008; 9(152):518-9.
30. Kuhn M, Campillos M, Letunic I, Jensen LJ, Bork P. A side effect resource to capture phenotypic effects of drugs. Mol Syst Biol. 2010; 6(1):343. doi:10.1038/msb.2009.98.
31. Cote R, Jones P, Apweiler R, Hermjakob H. The ontology lookup service, a lightweight cross-platform tool for controlled vocabulary queries. BMC Bioinformatics. 2006; 7(1):97. doi:10.1186/1471-2105-7-97.
32. Côté R, Reisinger F, Martens L, Barsnes H, Vizcaino JA, Hermjakob H. The ontology lookup service: bigger and better. Nucleic Acids Res. 2010; 38(suppl 2):155-60. doi:10.1093/nar/gkq331. http://nar.oxfordjournals.org/content/38/suppl_2/W155.full.pdf+html .
33. Fawcett T. An introduction to ROC analysis. Pattern Recogn Lett. 2006; 27(8):861-74. doi:10.1016/j.patrec.2005.10.010.
34. Köhler S, Schulz MH, Krawitz P, Bauer S, Doelken S, Ott CE, et al. Clinical diagnostics in human genetics with semantic similarity searches in ontologies. Am J Hum Genet. 2009; 85(4):457-64.
35. Smedley D, Oellrich A, Köhler S, Ruef B, Project SMG, Westerfield M, et al.Phenodigm: analyzing curated annotations to associate animal models with human diseases. Database. 2013; 2013:bat025. doi:10.1093/database/bat025. http://database.oxfordjournals.org/content/2013/bat025.full.pdf+html .
36. Harispe S, Ranwez S, Janaqi S, Montmain J. The semantic measures library and toolkit: fast computation of semantic similarity and relatedness using biomedical ontologies. Bioinformatics. 2014; 30(5):740-2. doi:10.1093/bioinformatics/btt581. http://bioinformatics.oxfordjournals.org/content/30/5/740.full.pdf+html .
37. Oti M, Brunner HG. The modular nature of genetic diseases. Clin Genet. 2007; 71:1-11.