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The DisGeNET knowledge platform for disease genomics: 2019 update.


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.

SUBMITTER: Pinero J 

PROVIDER: S-EPMC7145631 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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The DisGeNET knowledge platform for disease genomics: 2019 update.

Piñero Janet J   Ramírez-Anguita Juan Manuel JM   Saüch-Pitarch Josep J   Ronzano Francesco F   Centeno Emilio E   Sanz Ferran F   Furlong Laura I LI  

Nucleic acids research 20200101 D1


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 create  ...[more]

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