The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
The Human Gene Mutation Database: building a comprehensive mutation repository for clinical and molecular genetics, diagnostic testing and personalized genomic medicine
Open accessAbstract
The Human Gene Mutation Database (HGMD ® ) is a comprehensive collection of germline mutations in nuclear genes that underlie, or are associated with, human inherited disease. By June 2013, the database contained over 141,000 different lesions detected in over 5,700 different genes, with new mutation entries currently accumulating at a rate exceeding 10,000 per annum. HGMD was originally established in 1996 for the scientific study of mutational mechanisms in human genes. However, it has since acquired a much broader utility as a central unified disease-oriented mutation repository utilized by human molecular geneticists, genome scientists, molecular biologists, clinicians and genetic counsellors as well as by those specializing in biopharmaceuticals, bioinformatics and personalized genomics. The public version of HGMD ( https://www.hgmd.cf.ac.uk ) is freely available to registered users from academic institutions/non-profit organizations whilst the subscription version (HGMD Professional) is available to academic, clinical and commercial users under license via BIOBASE GmbH.
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Cites
A map of human genome variation from population-scale sequencing.
The 1000 Genomes Project Consortium (2010) · Nature · doi:10.1038/nature09534 · Cited by 7,877
An integrated map of genetic variation from 1,092 human genomes
The 1000 Genomes Project Consortium (2012) · Nature · doi:10.1038/nature11632 · Cited by 7,711
Evolutionary and biomedical insights from the rhesus macaque genome.
Gibbs, R. A., Rogers, J., Katze, M. G., Bumgarner, R., Weinstock, G. M., Mardis, E. R., Remington, K. A., Strausberg, R. L., Venter, J. C., Wilson, R. K., et al. (2007) · Science · doi:10.1126/science.1139247 · Cited by 1,403
Self-citationNCBI Reference Sequences: current status, policy and new initiatives
Pruitt, K. D., Tatusova, T., Klimke, W., & Maglott, D. R. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkn721 · Cited by 736 · cited 1×
“Provision of genomic reference sequences based on the NCBI RefSeqGene project (Pruitt et al. 2009), links to available protein structures and homology models, and mapping HGMD phenotypes to the Human Phenotype Ontology (HPO) are also regarded as priorities.”
Carrier testing for severe childhood recessive diseases by next-generation sequencing
Bell, C. J., Dinwiddie, D. L., Miller, N. A., Hateley, S. L., Ganusova, E. E., Mudge, J., Langley, R. J., Zhang, L., Lee, C. C., Schilkey, F. D., et al. (2011) · Science Translational Medicine · doi:10.1126/scitranslmed.3001756 · Cited by 706 · cited 1×
“In a clinical setting, HGMD is widely utilized by many groups in ongoing NGS diagnostic (Johnston et al. 2012, Calvo et al. 2012, Bell et al. 2011) and human genome sequencing (Tong et al. 2010; Kim et al. 2009) programmes.”
A highly annotated whole-genome sequence of a Korean individual
Kim, J.-I., Ju, Y. S., Park, H., Kim, S., Lee, S., Yi, J.-H., Mudge, J., Miller, N. A., Hong, D., Bell, C. J., et al. (2009) · Nature · doi:10.1038/nature08211 · Cited by 330
Cited by
Analysis of protein-coding genetic variation in 60,706 humans
Exome Aggregation Consortium, Lek, M., Karczewski, K. J., Minikel, E. V., Samocha, K. E., Banks, E., Fennell, T., O’Donnell-Luria, A. H., Ware, J. S., Hill, A. J., et al. (2016) · Nature · doi:10.1038/nature19057 · Cited by 9,587
Self-citationMutationTaster2: mutation prediction for the deep-sequencing age
Schwarz, J. M., Cooper, D. N., Schuelke, M., & Seelow, D. (2014) · Nature Methods · doi:10.1038/nmeth.2890 · Cited by 3,362
Self-citationREVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants
Ioannidis, N. M., Rothstein, J. H., Pejaver, V., Middha, S., McDonnell, S. K., Baheti, S., Musolf, A., Li, Q., Holzinger, E., Karyadi, D., et al. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2016.08.016 · Cited by 2,908
Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning
Alipanahi, B., Delong, A., Weirauch, M. T., & Frey, B. J. (2015) · Nature Biotechnology · doi:10.1038/nbt.3300 · Cited by 2,873
Predicting effects of noncoding variants with deep learning–based sequence model
Zhou, J., & Troyanskaya, O. G. (2015) · Nature Methods · doi:10.1038/nmeth.3547 · Cited by 2,338
Metadata
- Authors
- Stenson, P. D., Mort, M., Ball, E. V., Shaw, K., Phillips, A. D., & Cooper, D. N.
- Venue
- Human Genetics
- Published
- 2013-09-28
- Volume
- 133
- Issue
- 1
- Pages
- 1-9
- ISSN
- 0018-7348 (ISSN-L)
- 0340-6717
- 1432-1203
- OpenAlex
- W2045791858
- Cited by
- 1,346
- References
- 6
- FWCI
- 89.42
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- CoChat. (2026). Citation check: The Human Gene Mutation Database: building a comprehensive mutation repository for clinical and molecular genetics, diagnostic testing and personalized genomic medicine. https://app.cochat.ai/papers/10.1007/s00439-013-1358-4
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- Stenson, P. D., Mort, M., Ball, E. V., Shaw, K., Phillips, A. D., & Cooper, D. N. (2014). The Human Gene Mutation Database: building a comprehensive mutation repository for clinical and molecular genetics, diagnostic testing and personalized genomic medicine. Human Genetics. https://doi.org/10.1007/s00439-013-1358-4
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
