ArticleJournal of cheminformatics2021
IDSM ChemWebRDF: SPARQLing small-molecule datasets.
Article in Journal of cheminformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Centralized Review of Alzheimer's Disease and Related Dementias Biomedical Repositories and Computational Methods.Bioengineering (Basel, Switzerland) · 2026Review
- MolMeDB RDF: transforming a relational database about biological membranes to the RDF format to increase interoperability.Journal of cheminformatics · 2026Article
- Caver Web 2.0: analysis of tunnels and ligand transport in dynamic ensembles of proteins.Nucleic acids research · 2025Article
- A large collection of bioinformatics question-query pairs over federated knowledge graphs: methodology and applications.GigaScience · 2025Article
- The IDSM mass spectrometry extension: searching mass spectra using SPARQL.Bioinformatics (Oxford, England) · 2024Article
- Article
- Chemical Species Ontology for Data Integration and Knowledge Discovery.Journal of chemical information and modeling · 2023Article
- A comparison of approaches to accessing existing biological and chemical relational databases via SPARQL.Journal of cheminformatics · 2023Review
- Two years of explicit CiTO annotations.Journal of cheminformatics · 2023Article
- Annotation of biologically relevant ligands in UniProtKB using ChEBI.Bioinformatics (Oxford, England) · 2023Article
- Chemical reaction network knowledge graphs: the OntoRXN ontology.Journal of cheminformatics · 2022Article
- Review
- Fully automated virtual screening pipeline of FDA-approved drugs using Caver Web.Computational and structural biotechnology journal · 2022Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
The Resource Description Framework (RDF), together with well-defined ontologies, significantly increases data interoperability and usability. The SPARQL query language was introduced to retrieve requested RDF data and to explore links between them. Among other useful features, SPARQL supports federated queries that combine multiple independent data source endpoints. This allows users to obtain insights that are not possible using only a single data source. Owing to all of these useful features, many biological and chemical databases present their data in RDF, and support SPARQL querying. In our project, we primary focused on PubChem, ChEMBL and ChEBI small-molecule datasets. These datasets are already being exported to RDF by their creators. However, none of them has an official and currently supported SPARQL endpoint. This omission makes it difficult to construct complex or federated queries that could access all of the datasets, thus underutilising the main advantage of the availability of RDF data. Our goal is to address this gap by integrating the datasets into one database called the Integrated Database of Small Molecules (IDSM) that will be accessible through a SPARQL endpoint. Beyond that, we will also focus on increasing mutual interoperability of the datasets. To realise the endpoint, we decided to implement an in-house developed SPARQL engine based on the PostgreSQL relational database for data storage. In our approach, data are stored in the traditional relational form, and the SPARQL engine translates incoming SPARQL queries into equivalent SQL queries. An important feature of the engine is that it optimises the resulting SQL queries. Together with optimisations performed by PostgreSQL, this allows efficient evaluations of SPARQL queries. The endpoint provides not only querying in the dataset, but also the compound substructure and similarity search supported by our Sachem project. Although the endpoint is accessible from an internet browser, it is mainly intended to be used for programmatic access by other services, for example as a part of federated queries. For regular users, we offer a rich web application called ChemWebRDF using the endpoint. The application is publicly available at https://idsm.elixir-czech.cz/chemweb/ .
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.