Diseases 2.0: a weekly updated database of disease-gene associations from text mining and data integration.

ABSTRACT: The scientific knowledge about which genes are involved in which diseases grows rapidly, which makes it difficult to keep up with new publications and genetics datasets. The DISEASES database aims to provide a comprehensive overview by systematically integrating and assigning confidence scores to evidence for disease-gene associations from curated databases, genome-wide association studies (GWAS) and automatic text mining of the biomedical literature. Here, we present a major update to this resource, which greatly increases the number of associations from all these sources. This is especially true for the text-mined associations, which have increased by at least 9-fold at all confidence cutoffs. We show that this dramatic increase is primarily due to adding full-text articles to the text c

SUBMITTER: Grissa D 

PROVIDER: S-EPMC9216524 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature