Dataset Information

COVIDPUBGRAPH: A FAIR Knowledge Graph of COVID-19 Publications.

ABSTRACT: The rapid generation of large amounts of information about the coronavirus SARS-CoV-2 and the disease COVID-19 makes it increasingly difficult to gain a comprehensive overview of current insights related to the disease. With this work, we aim to support the rapid access to a comprehensive data source on COVID-19 targeted especially at researchers. Our knowledge graph, COVIDPUBGRAPH, an RDF knowledge graph of scientific publications, abides by the Linked Data and FAIR principles. The base dataset for the extraction is CORD-19, a dataset of COVID-19-related publications, which is updated regularly. Consequently, COVIDPUBGRAPH is updated biweekly. Our generation pipeline applies named entity recognition, entity linking and link discovery approaches to the original data. The current version of COVIDPUBGRAPH contains 268,108,670 triples and is linked to 9 other datasets by over 1 million links. In our use case studies, we demonstrate the usefulness of our knowledge graph for different applications. COVIDPUBGRAPH is publicly available under the Creative Commons Attribution 4.0 International license.

SUBMITTER: Pestryakova S

PROVIDER: S-EPMC9263802 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

COVIDPUBGRAPH: A FAIR Knowledge Graph of COVID-19 Publications.

Pestryakova Svetlana S Vollmers Daniel D Sherif Mohamed Ahmed MA Heindorf Stefan S Saleem Muhammad M Moussallem Diego D Ngomo Axel-Cyrille Ngonga AN

Scientific data 20220708 1

The rapid generation of large amounts of information about the coronavirus SARS-CoV-2 and the disease COVID-19 makes it increasingly difficult to gain a comprehensive overview of current insights related to the disease. With this work, we aim to support the rapid access to a comprehensive data source on COVID-19 targeted especially at researchers. Our knowledge graph, COVIDPUBGRAPH, an RDF knowledge graph of scientific publications, abides by the Linked Data and FAIR principles. The base dataset ...[more]

PMID: 35803947

Similar Datasets

Project description:ObjectiveTo discover candidate drugs to repurpose for COVID-19 using literature-derived knowledge and knowledge graph completion methods.MethodsWe propose a novel, integrative, and neural network-based literature-based discovery (LBD) approach to identify drug candidates from PubMed and other COVID-19-focused research literature. Our approach relies on semantic triples extracted using SemRep (via SemMedDB). We identified an informative and accurate subset of semantic triples using filtering rules and an accuracy classifier developed on a BERT variant. We used this subset to construct a knowledge graph, and applied five state-of-the-art, neural knowledge graph completion algorithms (i.e., TransE, RotatE, DistMult, ComplEx, and STELP) to predict drug repurposing candidates. The models were trained and assessed using a time slicing approach and the predicted drugs were compared with a list of drugs reported in the literature and evaluated in clinical trials. These models were complemented by a discovery pattern-based approach.ResultsAccuracy classifier based on PubMedBERT achieved the best performance (F1 = 0.854) in identifying accurate semantic predications. Among five knowledge graph completion models, TransE outperformed others (MR = 0.923, Hits@1 = 0.417). Some known drugs linked to COVID-19 in the literature were identified, as well as others that have not yet been studied. Discovery patterns enabled identification of additional candidate drugs and generation of plausible hypotheses regarding the links between the candidate drugs and COVID-19. Among them, five highly ranked and novel drugs (i.e., paclitaxel, SB 203580, alpha 2-antiplasmin, metoclopramide, and oxymatrine) and the mechanistic explanations for their potential use are further discussed.ConclusionWe showed that a LBD approach can be feasible not only for discovering drug candidates for COVID-19, but also for generating mechanistic explanations. Our approach can be generalized to other diseases as well as to other clinical questions. Source code and data are available at https://github.com/kilicogluh/lbd-covid.

Dataset Information

COVIDPUBGRAPH: A FAIR Knowledge Graph of COVID-19 Publications.

Publications

COVIDPUBGRAPH: A FAIR Knowledge Graph of COVID-19 Publications.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets