Abstract

Abstract One of the most pressing challenges in genomic medicine is to understand the role played by genetic variation in health and disease. Thanks to the exploration of genomic variants at large scale, hundreds of thousands of disease-associated loci have been uncovered. However, the identification of variants of clinical relevance is a significant challenge that requires comprehensive interrogation of previous knowledge and linkage to new experimental results. To assist in this complex task, we created DisGeNET (http://www.disgenet.org/), a knowledge management platform integrating and standardizing data about disease associated genes and variants from multiple sources, including the scientific literature. DisGeNET covers the full spectrum of human diseases as well as normal and abnormal traits. The current release covers more than 24 000 diseases and traits, 17 000 genes and 117 000 genomic variants. The latest developments of DisGeNET include new sources of data, novel data attributes and prioritization metrics, a redesigned web interface and recently launched APIs. Thanks to the data standardization, the combination of expert curated information with data automatically mined from the scientific literature, and a suite of tools for accessing its publicly available data, DisGeNET is an interoperable resource supporting a variety of applications in genomic medicine and drug R&D.

Keywords

GenomicsInteroperabilityBiologySuiteStandardizationData scienceIdentification (biology)Resource (disambiguation)Computational biologyRelevance (law)Precision medicineData integrationComputer scienceGenomeWorld Wide WebGeneticsData miningGene

MeSH Terms

Data MiningDatabasesGeneticDiseaseGenetic LociGenetic VariationGenomeHumanGenomicsHumansInternetUser-Computer Interface

Affiliated Institutions

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Publication Info

Year
2019
Type
article
Volume
48
Issue
D1
Pages
D845-D855
Citations
2620
Access
Closed

Social Impact

Social media, news, blog, policy document mentions

Citation Metrics

2620
OpenAlex
164
Influential
957
CrossRef

Cite This

Janet Piñero, Juan Manuel Ramírez‐Anguita, Josep Saüch-Pitarch et al. (2019). The DisGeNET knowledge platform for disease genomics: 2019 update. Nucleic Acids Research , 48 (D1) , D845-D855. https://doi.org/10.1093/nar/gkz1021

Identifiers

DOI
10.1093/nar/gkz1021
PMID
31680165
PMCID
PMC7145631

Data Quality

Data completeness: 90%