dc.contributor.author | Cacheiro, P | |
dc.contributor.author | Pava, D | |
dc.contributor.author | Parkinson, H | |
dc.contributor.author | VanZanten, M | |
dc.contributor.author | Wilson, R | |
dc.contributor.author | Gunes, O | |
dc.contributor.author | The International Mouse Phenotyping Consortium | |
dc.contributor.author | Smedley, D | |
dc.date.accessioned | 2024-07-15T09:27:37Z | |
dc.date.available | 2024-06-11 | |
dc.date.available | 2024-07-15T09:27:37Z | |
dc.date.issued | 2024-07-01 | |
dc.identifier.citation | Pilar Cacheiro, Diego Pava, Helen Parkinson, Maya VanZanten, Robert Wilson, Osman Gunes, the International Mouse Phenotyping Consortium, Damian Smedley; Computational identification of disease models through cross-species phenotype comparison. Dis Model Mech 1 June 2024; 17 (6): dmm050604. doi: https://doi.org/10.1242/dmm.050604 | en_US |
dc.identifier.uri | https://qmro.qmul.ac.uk/xmlui/handle/123456789/98117 | |
dc.description.abstract | The use of standardised phenotyping screens to identify abnormal phenotypes in mouse knockouts, together with the use of ontologies to describe such phenotypic features, allows the implementation of an automated and unbiased pipeline to identify new models of disease by performing phenotype comparisons across species. Using data from the International Mouse Phenotyping Consortium (IMPC), approximately half of mouse mutants are able to mimic, at least partially, the human ortholog disease phenotypes as computed by the PhenoDigm algorithm. We found the number of phenotypic abnormalities in the mouse and the corresponding Mendelian disorder, the pleiotropy and severity of the disease, and the viability and zygosity status of the mouse knockout to be associated with the ability of mouse models to recapitulate the human disorder. An analysis of the IMPC impact on disease gene discovery through a publication-tracking system revealed that the resource has been implicated in at least 109 validated rare disease-gene associations over the last decade. | en_US |
dc.language | eng | |
dc.publisher | The Company of Biologists | en_US |
dc.relation.ispartof | Dis Model Mech | |
dc.rights | This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed. | |
dc.subject | Cross-species phenotype comparison | en_US |
dc.subject | Mendelian disorders | en_US |
dc.subject | Mouse models | en_US |
dc.subject | Animals | en_US |
dc.subject | Phenotype | en_US |
dc.subject | Disease Models, Animal | en_US |
dc.subject | Humans | en_US |
dc.subject | Species Specificity | en_US |
dc.subject | Computational Biology | en_US |
dc.subject | Mice | en_US |
dc.subject | Mice, Knockout | en_US |
dc.subject | Algorithms | en_US |
dc.title | Computational identification of disease models through cross-species phenotype comparison. | en_US |
dc.type | Article | en_US |
dc.rights.holder | © 2024. Published by The Company of Biologists Ltd | |
dc.identifier.doi | 10.1242/dmm.050604 | |
pubs.author-url | https://www.ncbi.nlm.nih.gov/pubmed/38881316 | en_US |
pubs.issue | 6 | en_US |
pubs.notes | Not known | en_US |
pubs.publication-status | Published | en_US |
pubs.volume | 17 | en_US |
dcterms.dateAccepted | 2024-06-11 | |
rioxxterms.funder | Default funder | en_US |
rioxxterms.identifier.project | Default project | en_US |
qmul.funder | Mouse Phenotyping Informatics Infrastructure - Data acquisition, integration, analysis and translation of high throughput mammalian phenotyping data.::National Human Genome Research Institute | en_US |
rioxxterms.funder.project | b215eee3-195d-4c4f-a85d-169a4331c138 | en_US |