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

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• 作者：Robert Hoehndorf (1) (2)
  Michael Gruenberger (3)
  Georgios V Gkoutos (4)
  Paul N Schofield (3)
  
  1. Computational Bioscience Research Center ; King Abdullah University of Science and Technology ; 4700 KAUST ; Thuwal ; 23955-6900 ; Saudi Arabia
  2. Computer ; Electrical and Mathematical Sciences & Engineering Division ; King Abdullah University of Science and Technology ; 4700 KAUST ; Thuwal ; 23955-6900 ; Saudi Arabia
  3. Department of Computer Science ; Aberystwyth University ; Llandinam Building ; Aberystwyth ; SY23 3DB ; UK
  4. Department of Physiology ; Development & Neuroscience ; University of Cambridge ; Downing Street ; Cambridge ; CB2 3EG ; UK
  
• 关键词：Phenotype ; Semantic similarity ; Ontology
• 刊名：Journal of Biomedical Semantics
• 出版年：2015
• 出版时间：December 2015
• 年：2015
• 卷：6
• 期：1
• 全文大小：336 KB
• 参考文献：1. Schofield, PN, Hoehndorf, R, Gkoutos, GV (2012) Mouse genetic and phenotypic resources for human genetics. Hum Mutat. 33: pp. 826-36 2/humu.22077" target="_blank" title="It opens in new window">CrossRef
  2. Gkoutos, GV, Schofield, PN, Hoehndorf, R (2012) Computational tools for comparative phenomics: the role and promise of ontologies. Mamm Genome. 23: pp. 669-79 2-9404-4" target="_blank" title="It opens in new window">CrossRef
  3. Pesquita, C, Faria, D, Falcao, AO, Lord, P, Couto, FM (2009) Semantic similarity in biomedical ontologies. PLoS Comput Biol. 5: pp. 1000443 CrossRef
  4. Hoehndorf, R, Hardy, NW, Osumi-Sutherland, D, Tweedie, S, Schofield, PN, Gkoutos, GV (2013) Systematic analysis of experimental phenotype data reveals gene functions. PLoS ONE. 8: pp. 60847 CrossRef
  5. Hoehndorf, R, Schofield, PN, Gkoutos, GV (2011) Phenomenet: a whole-phenome approach to disease gene discovery. Nucleic Acids Res. 39: pp. 119 CrossRef
  6. Hoehndorf, R, Schofield, PN, Gkoutos, GV (2013) An integrative, translational approach to understanding rare and orphan genetically based diseases. Interface Focus. 3: pp. 20120055 2012.0055" target="_blank" title="It opens in new window">CrossRef
  7. Chen, Cc-K, Mungall, CcJ, Gkoutos, GcV, Doelken, ScC, K枚hler, S, Ruef, BcJ (2012) Mousefinder: Candidate disease genes from mouse phenotype data. Hum Mutation. 33: pp. 858-66 2/humu.22051" target="_blank" title="It opens in new window">CrossRef
  8. Zemojtel, T, K枚hler, S, Mackenroth, L, J盲ger, M, Hecht, J, Krawitz, P (2014) Effective diagnosis of genetic disease by computational phenotype analysis of the disease-associated genome. Sci Transl Med. 6: pp. 252-123 26/scitranslmed.3009262" target="_blank" title="It opens in new window">CrossRef
  9. Hoehndorf, R, Hiebert, T, Hardy, NW, Schofield, PN, Gkoutos, GV, Dumontier, M (2014) Mouse model phenotypes provide information about human drug targets. Bioinformatics. 30: pp. 719-25 CrossRef
  10. Dwinell, MR, Worthey, EA, Shimoyama, M, Bakir-Gungor, B, DePons, J, Laulederkind, S (2009) The rat genome database 2009: variation, ontologies and pathways. Nucleic Acids Res. 37: pp. 744-49 2" target="_blank" title="It opens in new window">CrossRef
  11. Gaudet, P, Fey, P, Basu, S, Bushmanova, YA, Dodson, R, Sheppard, KA (2011) dictybase update 2011: web 2.0 functionality and the initial steps towards a genome portal for the amoebozoa. Nucleic Acids Res. 39: pp. 620-4 CrossRef
  12. Robinson, PN, K枚hler, S, Bauer, S, Seelow, D, Horn, D, Mundlos, S (2008) The human phenotype ontology: a tool for annotating and analyzing human hereditary disease. Am J Hum Genet. 83: pp. 610-5 2008.09.017" target="_blank" title="It opens in new window">CrossRef
  13. Smith, CL, Eppig, JT (2012) The mammalian phenotype ontology as a unifying standard for experimental and high-throughput phenotyping data. Mamm Genome. 23: pp. 653-68 2-9421-3" target="_blank" title="It opens in new window">CrossRef
  14. Mungall, C, Gkoutos, G, Smith, C, Haendel, M, Lewis, S, Ashburner, M (2010) Integrating phenotype ontologies across multiple species. Genome Biol. 11: pp. 2 2010-11-1-r2" target="_blank" title="It opens in new window">CrossRef
  15. Mungall, C, Torniai, C, Gkoutos, G, Lewis, S, Haendel, M (2012) Uberon, an integrative multi-species anatomy ontology. Genome Biol. 13: pp. 5 2012-13-1-r5" target="_blank" title="It opens in new window">CrossRef
  16. Ashburner, M, Ball, CA, Blake, JA, Botstein, D, Butler, H, Cherry, MJ (2000) Gene ontology: tool for the unification of biology. Nat Genet. 25: pp. 25-29 CrossRef
  17. Gkoutos, GV, Green, EC, Mallon, A-MM, Hancock, JM, Davidson, D (2005) Using ontologies to describe mouse phenotypes. Genome Biol. 6: pp. 5
  18. Hayamizu, TF, Mangan, M, Corradi, JP, Kadin, JA, Ringwald, M (2005) The adult mouse anatomical dictionary: a tool for annotating and integrating data. Genome Biol. 6: pp. R29 2005-6-3-r29" target="_blank" title="It opens in new window">CrossRef
  19. Rosse, C, Mejino, JLV (2003) A reference ontology for biomedical informatics: the Foundational Model of Anatomy. J Biomed Inform. 36: pp. 478-500 2003.11.007" target="_blank" title="It opens in new window">CrossRef
  20. Hoehndorf, R, Oellrich, A, Rebholz-Schuhmann, D (2010) Interoperability between phenotype and anatomy ontologies. Bioinformatics. 26: pp. 3112-8 CrossRef
  21. Horridge, M, Bechhofer, S, Noppens, O (2007) Igniting the OWL 1.1 touch paper: The OWL API. Proceedings of OWLED 2007: third international workshop on OWL experiences and directions.. CEUR-WS.org, Aachen, Germany
  22. Kazakov, Y, Kr枚tzsch, M, Simancik, F (2014) The incredible elk. J Automated Reasoning. 53: pp. 1-61
  23. Pesquita, C, Faria, D, Bastos, H, Ferreira, A, Falcao, A, Couto, F (2008) Metrics for GO based protein semantic similarity: a systematic evaluation. BMC Bioinformatics. 9: pp. 4 2105-9-S5-S4" target="_blank" title="It opens in new window">CrossRef
  24. Oellrich, A, Hoehndorf, R, Gkoutos, GV, Rebholz-Schuhmann, D (2012) Improving disease gene prioritization by comparing the semantic similarity of phenotypes in mice with those of human diseases. PLoS ONE. 7: pp. 38937 CrossRef
  25. Bello, SM, Richardson, JE, Davis, AP, Wiegers, TC, Mattingly, CJ, Dolan, ME (2012) Disease model curation improvements at mouse genome informatics. Database. 2012: pp. 063 CrossRef
  26. Harris, TW, Antoshechkin, I, Bieri, T, Blasiar, D, Chan, J, Chen, WJ (2010) WormBase: a comprehensive resource for nematode research. Nucleic Acids Res. 38: pp. 463-7 2" target="_blank" title="It opens in new window">CrossRef
  27. Cherry, JM, Adler, C, Ball, C, Chervitz, SA, Dwight, SS, Hester, ET (1998) SGD: Saccharomyces genome database. Nucleic Acids Res. 26: pp. 73-9 26.1.73" target="_blank" title="It opens in new window">CrossRef
  28. Amberger, J, Bocchini, C, Hamosh, A (2011) A new face and new challenges for Online Mendelian Inheritance in Man (OMIM). Hum Mutat. 32: pp. 564-7 2/humu.21466" target="_blank" title="It opens in new window">CrossRef
  29. Weinreich, SS, Mangon, R, Sikkens, JJ, Teeuw, ME, Cornel, MC (2008) Orphanet: a european database for rare diseases. Ned Tijdschr Geneeskd. 9: pp. 518-9
  30. Kuhn, M, Campillos, M, Letunic, I, Jensen, LJ, Bork, P (2010) A side effect resource to capture phenotypic effects of drugs. Mol Syst Biol. 6: pp. 343
  31. Cote, R, Jones, P, Apweiler, R, Hermjakob, H (2006) The ontology lookup service, a lightweight cross-platform tool for controlled vocabulary queries. BMC Bioinformatics. 7: pp. 97 2105-7-97" target="_blank" title="It opens in new window">CrossRef
  32. C么t茅, R, Reisinger, F, Martens, L, Barsnes, H, Vizcaino, JA, Hermjakob, H (2010) The ontology lookup service: bigger and better. Nucleic Acids Res. 38: pp. 155-60 CrossRef
  33. Fawcett, T (2006) An introduction to ROC analysis. Pattern Recogn Lett. 27: pp. 861-74 2005.10.010" target="_blank" title="It opens in new window">CrossRef
  34. K枚hler, S, Schulz, MH, Krawitz, P, Bauer, S, Doelken, S, Ott, CE (2009) Clinical diagnostics in human genetics with semantic similarity searches in ontologies. Am J Hum Genet. 85: pp. 457-64 2009.09.003" target="_blank" title="It opens in new window">CrossRef
  35. Smedley, D, Oellrich, A, K枚hler, S, Ruef, B, Project, SMG (2013) Phenodigm: analyzing curated annotations to associate animal models with human diseases. Database. 2013: pp. bat025 25" target="_blank" title="It opens in new window">CrossRef
  36. Harispe, S, Ranwez, S, Janaqi, S, Montmain, J (2014) The semantic measures library and toolkit: fast computation of semantic similarity and relatedness using biomedical ontologies. Bioinformatics. 30: pp. 740-2 CrossRef
  37. Oti, M, Brunner, HG (2007) The modular nature of genetic diseases. Clin Genet. 71: pp. 1-11 2006.00708.x" target="_blank" title="It opens in new window">CrossRef
  
• 刊物主题：Algorithms; Computer Appl. in Life Sciences; Data Mining and Knowledge Discovery; Computational Biology/Bioinformatics; Bioinformatics; Combinatorial Libraries;
• 出版者：BioMed Central
• ISSN：2041-1480

文摘

Background Semantic similarity measures over phenotype ontologies have been demonstrated to provide a powerful approach for the analysis of model organism phenotypes, the discovery of animal models of human disease, novel pathways, gene functions, druggable therapeutic targets, and determination of pathogenicity. Results We have developed PhenomeNET 2, a system that enables similarity-based searches over a large repository of phenotypes in real-time. It can be used to identify strains of model organisms that are phenotypically similar to human patients, diseases that are phenotypically similar to model organism phenotypes, or drug effect profiles that are similar to the phenotypes observed in a patient or model organism. PhenomeNET 2 is available at http://aber-owl.net/phenomenet. Conclusions Phenotype-similarity searches can provide a powerful tool for the discovery and investigation of molecular mechanisms underlying an observed phenotypic manifestation. PhenomeNET 2 facilitates user-defined similarity searches and allows researchers to analyze their data within a large repository of human, mouse and rat phenotypes.