OMIM.org: leveraging knowledge across phenotype–gene relationships

By Joanna S. Amberger, Carol A. Bocchini, Alan F. Scott, Ada Hamosh. Nucleic Acids Res., 2018

914 citations recorded by the source corpus.

Abstract For over 50 years Mendelian Inheritance in Man has chronicled the collective knowledge of the field of medical genetics. It initially cataloged the known X-linked, autosomal recessive and autosomal dominant inherited disorders, but grew to be the primary repository of curated information on both genes and genetic phenotypes and the relationships between them. Each phenotype and gene is given a separate entry assigned a stable, unique identifier. The entries contain structured summaries of new and important information based on expert review of the biomedical literature. OMIM.org provides interactive access to the knowledge repository, including genomic coordinate searches of the gene map, views of genetic heterogeneity of phenotypes in Phenotypic Series, and side-by-side comparisons of clinical synopses. OMIM.org also supports computational queries via a robust API. All entries have extensive targeted links to other genomic resources and additional references. Updates to OMIM can be found on the update list or followed through the MIMmatch service. Updated user guides and tutorials are available on the website. As of September 2018, OMIM had over 24,600 entries, and the OMIM Morbid Map Scorecard had 6,259 molecularized phenotypes connected to 3,961 genes.

Subfields: Genetics, Molecular Biology, Pathology and Forensic Medicine

View Paper: https://www.semanticscholar.org/paper/8426d840dbad3b6c29d7bc070847f76609462bef

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Citations in the corpus

ClinVar: improvements to accessing data (2019, background): “Each gene is linked to Entrez Gene (10) and OMIM® (11), to expedite access to more information about the gene.”
Information Retrieval: A Biomedical and Health Perspective (2020, background): “One noteworthy title in this collection is Online Mendelian Inheritance in Man (OMIM),74 which is now maintained at a separate site,75 although the version in NCBI Bookshelf is kept up to date [26].”
The Human Phenotype Ontology in 2021 (2020, methodology): “The HPO provides annotations to diseases defined by Online Mendelian Inheritance in Man (OMIM) (17), nearly all of which are monogenic (Mendelian) diseases.”
Genenames.org: the HGNC resources in 2023 (2022, background): “In addition, the HGNC data section may include curator notes and/or links to gene groups curated by the HGNC. HGNC Symbol Reports also provide numerous useful external data links to biomedical resources such as NCBI Gene (5), Ensembl (6) UniProt (7), GeneCards (8), RNAcentral (9), UCSC genome browse”
FlyBase: a guided tour of highlighted features (2022, background): “2019), disease model-associated genes, and alleles annotated with DO terms; search terms can include any of those, as well as OMIM terms or disease synonyms (Amberger et al. 2019).”
Genenames.org: the HGNC and VGNC resources in 2021 (2020, background): “As OMIM has taken over the cataloguing and assignment of human phenotype symbols, and our set of ‘phenotype’ symbols was not complete, nor being regularly updated, we made the decision to withdraw all of these entries.”
The International Mouse Phenotyping Consortium: comprehensive knockout phenotyping underpinning the study of human disease (2022, result): “summarises the number of IMPC mouse knockouts with a one-to-one human orthologue associated with OMIM /Orphanet disorders (41,42) and the corresponding PhenoDigm results according to DR17.”
FlyBase: updates to the Drosophila melanogaster knowledge base (2020, background): “The new pipeline combines three sets of data: (i) D. melanogaster-tohuman orthology relationships from DIOPT (6); (ii) human gene-to-phenotype relationships from OMIM (14); and (iii) OMIM phenotype cross-references within the Disease Ontology (DO) (15).”
The STRING database in 2023: protein–protein association networks and functional enrichment analyses for any sequenced genome of interest (2022, background): “Lastly, the ‘textmining’ channel is the result of parsing full-text articles from the PMC Open Access Subset (up to April 2022), PubMed abstracts (up to August 2022), as well as summary texts from OMIM (44) and SGD (45) entry descriptions.”
The DisGeNET knowledge platform for disease genomics: 2019 update (2019, background): “Two genes are annotated to the disease in Or-phanet (DMD, LTB4, https://www.orpha.net/consor/ cgi-bin/Disease Genes Simple.php?lng=EN&LnkId= 13913&Typ=Pat&diseaseType=Gen&from=rightMenu) and one in OMIM (DMD, https://www.omim. org/entry/310200?search=duchenne%20muscular% 20dystrophy&highlight=duchen”