Reader in Biomedical Informatics
Tel: 01223 333878, Fax: +44 (0)1223 333840, E-mail: firstname.lastname@example.org
The main focus of the group is the use of mouse models to understand human diseases and gene function, particularly fetal-overgrowth disorders such as Beckwith-Wiedemann syndrome. We are involved in the development of approaches and informatics tools to capture and analyse phenotypic data from mice, particularly in the area of histopathology, and are working with the International Knockout Mouse Consortium and the International Mouse Phenotyping Consortium on data capture, integration and analysis.
Ontology development and phenotype informatics tools
Comparing phenotypes between species potentially provides invaluable insights into the pathobiology and etiology of human disease. Phenotypic characterisation of, for example, mouse and zebrafish mutants can provide information that can be used to prioritise gene lists derived from human genome-wide association studies, allow the dissection of loci involved in copy number-variation lesions, and provide functional validation of disease gene candidates, as well as insights into basic biological processes. The ability to cross the species divide has long been a thorny problem, as human and model organism phenotypes are described using different formal ontologies and conceptual approaches. To address this, we are working to develop a series of ontologies and tools that use those ontologies, allowing the seamless integration of phenotypic data between species.
Mammalian pathology ontology – MPATH
George Gkoutos, John Sundberg, Michael Gruenberger
MPATH, the mammalian pathology ontology was initially designed to describe the pathological features of histological slides of mouse lesions in Pathbase, a database of mutant mouse pathology. The ontology has been developed further since and now covers all classes of pathological lesion, and used in combination with the appropriate anatomy ontology and qualifiers from the phenotype and trait ontology, PATO, can be used to describe any histopathological lesion in mammals. The most recent version of MPATH can be obtained from Google Code or the Open Biological and Biomedical Ontologies (OBO) web site.
George Gkoutos, Robert Hoehndorf
We have developed a semantic approach to integrating phenotype ontologies, Phenomenet, which uses formal definitions of ontology classes to generate equivalences between phenotypes in species-specific ontologies. These formal definitions are generated using the Phenotype and Trait ontology, PATO, together with multi-species or species-agnostic ontologies, such as MPATH, and the Gene Ontology, permitting bridging between the ontologies. Use of the full semantic information in these ontologies provides a powerful way to integrate and query phenotypic information. Phenomenet has been made available on the Phenome Browser.
We work closely on ontology development with Dr Peter Robinson (Human Phenotype Ontology), Prof Michael Ashburner (Dept Genetics, Cambridge), Prof Monte Westerfield (University of Oregon), and Prof Suzi Lewis (Lawrence Berkeley Laboratory), and have long term collaborations with Prof John Sundberg (The Jackson Laboratory).
Work on radiobiology legacy databases and community resources is the result of long-term, ongoing collaborations with Dr Bernd Grosche of the German Federal Office for Radiation Protection, and Prof Mike Atkinson and Dr Soile Tapio, of the Institute of Radiation Biology, Helmholtz Zentrum München.
Informatics work in the Group is currently funded by the BBSRC, NIH and the European Commission.
Selected recent papers
Hoehndorf R, Dumontier R, Oellrich A, Rebholz-Schuhmann D, Schofield PN, Gkoutos GV. (2011) Interoperability between biomedical ontologies through relation expansion, upper-level ontologies and automatic reasoning. PLoS One 6:e22006.
Hoehndorf R, Schofield PN, Gkoutos GV. (2011) PhenomeNET: A whole-phenome approach to disease gene discovery. Nucl Acids Res. Epub doi:10.1093/nar/gkr538
Hoehndorf R, Dumontier M, et al. (2011) A common layer of interoperability for biomedical ontologies based on OWL EL. Bioinformatics 27:1001-1008.
Sundberg J, Berndt A, Sundberg B, et al. (2011) The mouse as a model for understanding chronic diseases of aging: the histopathologic basis of aging in inbred mice. Pathobiology of Aging & Age-related Diseases 1:7179.
Swertz MA, van der Velde KJ, Tesson BM, et al. (2010) XGAP: a uniform and extensible data model and software platform for genotype and phenotype experiments. Genome Biol 11:R27.
Schofield PN, Gkoutos GV, Gruenberger M, Sundberg JP, Hancock JM. (2010) Phenotype ontologies for mouse and man; bridging the semantic gap. Dis Model Mech 3:281-289.
Schofield PN, Gruenberger M, Sundberg JP. (2010) Pathbase and the MPATH ontology: community resources for mouse histopathology. Vet Pathol 47:1016-1020.
Schofield PN, Dubus P, Klein L, et al. (2010) Pathology of the laboratory mouse: an international workshop on challenges for high throughput phenotyping. Toxicol Pathol 39:559-562.
Gkoutos GV, Mungall C, Dolken S, Ashburner M, Lewis S, et al. (2009) Entity/quality-based logical definitions for the human skeletal phenome using PATO. Conf Proc IEEE Eng Med Biol Soc 2009:7069-7072.
Sundberg JP, Schofield PN. (2009) One medicine, one pathology, and the one health concept. J Am Vet Med Assoc 234:1530-1531.
Science Commons, data and resource sharing
As part of the CASIMIR project, funded as a coordination action by the European Commission, we looked at issues affecting the mouse commons – accessibility to data and bioresources by the world's scientific community, and the problems presented by a combination of the globalisation of science and the generation of very large datasets. This included both the technical issues of data integration and those raised by intellectual-property considerations and social cultures of sharing. The issues of funding of the infrastructure for sharing were also considered by the group, and the first in a planned series of policy papers on the mouse commons published.
Schofield PN, Tapio S, Grosche B. (2011) Archiving lessons from radiobiology. Nature 468:634.
Gaudet P, Bairoch A, Field D, Sansone S-A, Taylor C, Attwood TK, et al. (2011) Towards BioDBcore: a community-defined information specification for biological databases. Database. doi:10.1093/database/baq027
Tapio S, Schofield PN, Adelmann C, Atkinson MJ, Bard JLB, et al. (2011) The European Radiobiological Archives: online access to data from radiobiological experiments. Radiat Res 175:526-531.
International Arabidopsis Informatics Consortium. (2011) An international bioinformatics infrastructure to underpin the Arabidopsis community. Plant Cell 22:2530-2536.
Schofield PN, Eppig JT, Huala E, Hrabe de Angelis M, Harvey M, Davidson D, Weaver T, Brown SD, Smedley D, Rosenthal N, Schughart K, Aidinis V, Tocchini-Valentini G, Hancock JM, the CASIMIR consortium. (2010) Sustaining the data and bioresource commons. Science 330:592-593.
Schofield PN, Bubela T, Weaver T, Portilla L, Brown SD, Hancock JM, Einhorn D, Tocchini-Valentini G, Hrabe de Angelis M, Rosenthal, N. (2009). Post-publication sharing of data and tools. Nature 461:171-3.
Birney E, Hudson TJ, Green ED, et al. (2009) Prepublication data sharing, Nature 461:168-170.
Smedley D, Schofield P, Chen CK, et al. (2010) Finding and sharing: new approaches to registries of databases and services for the biomedical sciences. Database. doi:10.1093/database/baq014