A - Papers appearing in refereed journals
Shefchek, K. A., Harris, N. L., Gargano, M., Matentzoglu, N., Unni, D., Brush, M., Keith, D., Conlin, T., Vasilevsky, N., Zhang, X. A., Balhoff, J. P., Babb, L., Bello, S. M., Blau, H., Bradford, Y., Carbon, S., Carmody, L., Chan, L. E., Cipriani, V., Cuzick, A., Rocca, M. D., Dunn, N., Essaid, S., Fey, P., Grove, C., Gourdine, J., Hamosh, A., Harris, M., Helbig, I., Hoatlin, M., Joachimiak, M., Jupp, S., Lett, K. B., Lewis, S. E., McNamara, C., Pendlington, Z. M., Pilgrim, C., Putman, T., Ravanmehr, V., Reese, J., Riggs, E., Robb, S., Roncaglia, P., Seager, J., Segerdell, E., Similuk, M., Storm, A. L., Thaxon, C., Thessen, A., Jacobsen, J. O. B., McMurry, J. A., Groza, T., Köhler, S., Smedley, D., Robinson, P. N., Mungall, C. J., Haendel, M. A., Munoz-Torres, M. C. and Osumi-Sutherland, D. 2020. The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species. Nucleic Acids Research. 48 (D1), p. D704–D715. https://doi.org/10.1093/nar/gkz997
Authors | Shefchek, K. A., Harris, N. L., Gargano, M., Matentzoglu, N., Unni, D., Brush, M., Keith, D., Conlin, T., Vasilevsky, N., Zhang, X. A., Balhoff, J. P., Babb, L., Bello, S. M., Blau, H., Bradford, Y., Carbon, S., Carmody, L., Chan, L. E., Cipriani, V., Cuzick, A., Rocca, M. D., Dunn, N., Essaid, S., Fey, P., Grove, C., Gourdine, J., Hamosh, A., Harris, M., Helbig, I., Hoatlin, M., Joachimiak, M., Jupp, S., Lett, K. B., Lewis, S. E., McNamara, C., Pendlington, Z. M., Pilgrim, C., Putman, T., Ravanmehr, V., Reese, J., Riggs, E., Robb, S., Roncaglia, P., Seager, J., Segerdell, E., Similuk, M., Storm, A. L., Thaxon, C., Thessen, A., Jacobsen, J. O. B., McMurry, J. A., Groza, T., Köhler, S., Smedley, D., Robinson, P. N., Mungall, C. J., Haendel, M. A., Munoz-Torres, M. C. and Osumi-Sutherland, D. |
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Abstract | In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven’t been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to facilitate translational research. Launched in 2015, Monarch has grown with regards to data (new organisms, more sources, better modeling); new API and standards; ontologies (new Mondo unified disease ontology, improvements to ontologies such as HPO and uPheno); user interface (a redesigned website); and community development. Monarch data, algorithms and tools are being used and extended by resources such as GA4GH and NCATS Translator, among others, to aid mechanistic discovery and diagnostics. |
Year of Publication | 2020 |
Journal | Nucleic Acids Research |
Journal citation | 48 (D1), p. D704–D715 |
Digital Object Identifier (DOI) | https://doi.org/10.1093/nar/gkz997 |
PubMed ID | 31701156 |
PubMed Central ID | PMC7056945 |
Open access | Published as ‘gold’ (paid) open access |
Funder | Biotechnology and Biological Sciences Research Council |
Publisher's version | Copyright license Open Government Licence |
Output status | Published |
Publication dates | |
Online | 08 Nov 2019 |
Publication process dates | |
Accepted | 14 Oct 2019 |
Publisher | Oxford University Press (OUP) |
Other file | The%20Monarch%20Initiative%20in%202019%3A%20an%20integrative%20data%20and%20analytic%20platform%20connecting%20phenotypes%20to%20genotypes%20across%20species.%20.pdf |
ISSN | 0305-1048 |
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