Entity/quality-based Logical Definitions for the Human Skeletal Phenome Using PATO

Overview

Journal Annu Int Conf IEEE Eng Med Biol Soc

Specialty Biomedical Engineering

Date 2009 Dec 8

PMID 19964203

Citations 49

Authors

Georgios V Gkoutos

Chris Mungall

Sandra Dolken

Michael Ashburner

Suzanna Lewis

John Hancock

Paul Schofield

Sebastian Kohler

Peter N Robinson

Affiliations

Soon will be listed here.

Abstract

This paper describes an approach to providing computer-interpretable logical definitions for the terms of the Human Phenotype Ontology (HPO) using PATO, the ontology of phenotypic qualities, to link terms of the HPO to the anatomic and other entities that are affected by abnormal phenotypic qualities. This approach will allow improved computerized reasoning as well as a facility to compare phenotypes between different species. The PATO mapping will also provide direct links from phenotypic abnormalities and underlying anatomic structures encoded using the Foundational Model of Anatomy, which will be a valuable resource for computational investigations of the links between anatomical components and concepts representing diseases with abnormal phenotypes and associated genes.

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References

Robinson P, Kohler 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. PMC: 2668030. DOI: 10.1016/j.ajhg.2008.09.017. View

Sundberg J, Sundberg B, Schofield P . Integrating mouse anatomy and pathology ontologies into a phenotyping database: tools for data capture and training. Mamm Genome. 2008; 19(6):413-9. PMC: 2844541. DOI: 10.1007/s00335-008-9123-z. View

Bard J, Rhee S, Ashburner M . An ontology for cell types. Genome Biol. 2005; 6(2):R21. PMC: 551541. DOI: 10.1186/gb-2005-6-2-r21. View

Jiang X, Liu B, Jiang J, Zhao H, Fan M, Zhang J . Modularity in the genetic disease-phenotype network. FEBS Lett. 2008; 582(17):2549-54. DOI: 10.1016/j.febslet.2008.06.023. View

Bodenreider O, Hayamizu T, Ringwald M, de Coronado S, Zhang S . Of mice and men: aligning mouse and human anatomies. AMIA Annu Symp Proc. 2006; :61-5. PMC: 1560846. View

Zhang S, Bodenreider O . Experience in Aligning Anatomical Ontologies. Int J Semant Web Inf Syst. 2008; 3(2):1-26. PMC: 2575410. DOI: 10.4018/jswis.2007040101. View

Kohler S, Bauer S, Horn D, Robinson P . Walking the interactome for prioritization of candidate disease genes. Am J Hum Genet. 2008; 82(4):949-58. PMC: 2427257. DOI: 10.1016/j.ajhg.2008.02.013. View

Sundberg J, Schofield P . One medicine, one pathology, and the one health concept. J Am Vet Med Assoc. 2009; 234(12):1530-1. PMC: 3804058. DOI: 10.2460/javma.234.12.1530. View

Ashburner M, Ball C, Blake J, Botstein D, Butler H, Cherry J . Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet. 2000; 25(1):25-9. PMC: 3037419. DOI: 10.1038/75556. View

10.

Amberger J, Bocchini C, Scott A, Hamosh A . McKusick's Online Mendelian Inheritance in Man (OMIM). Nucleic Acids Res. 2008; 37(Database issue):D793-6. PMC: 2686440. DOI: 10.1093/nar/gkn665. View

11.

Rosenthal N, Brown S . The mouse ascending: perspectives for human-disease models. Nat Cell Biol. 2007; 9(9):993-9. DOI: 10.1038/ncb437. View

12.

Rosse C, Mejino Jr J . A reference ontology for biomedical informatics: the Foundational Model of Anatomy. J Biomed Inform. 2004; 36(6):478-500. DOI: 10.1016/j.jbi.2003.11.007. View

13.

Oti M, Huynen M, Brunner H . Phenome connections. Trends Genet. 2008; 24(3):103-6. DOI: 10.1016/j.tig.2007.12.005. View

14.

Araki S, Hayashi M, Tamagawa K, Saito M, Kato S, Komori T . Neuropathological analysis in spinal muscular atrophy type II. Acta Neuropathol. 2003; 106(5):441-8. DOI: 10.1007/s00401-003-0743-9. View

15.

Smith C, Goldsmith C, Eppig J . The Mammalian Phenotype Ontology as a tool for annotating, analyzing and comparing phenotypic information. Genome Biol. 2005; 6(1):R7. PMC: 549068. DOI: 10.1186/gb-2004-6-1-r7. View