ArticlePloS one2011
The chemical information ontology: provenance and disambiguation for chemical data on the biological semantic web.
Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
49 citing papers in PubMed.
- Towards the digital analytical sciences in chemistry and biochemistry: from FAIR data ecosystems to artificial intelligence.Analytical and bioanalytical chemistry · 2026Review
- tmQM-RDF Data Set: A Knowledge Graph Representing Transition Metal Complexes.Journal of chemical information and modeling · 2026Article
- MolMeDB RDF: transforming a relational database about biological membranes to the RDF format to increase interoperability.Journal of cheminformatics · 2026Article
- An exploratory study combining Virtual Reality and Semantic Web for life science research using Graph2VR.Database : the journal of biological databases and curation · 2025Article
- Linking Research Data with Physically Preserved Research Materials in Chemistry.Scientific data · 2025Article
- Beyond chemical structures: lessons and guiding principles for the next generation of molecular databases.Chemical science · 2025Review
- Linking behaviour change techniques to mechanisms of action: Using the Theory and Techniques Tool alongside the Behaviour Change Intervention Ontology.Wellcome open research · 2025Article
- From papers to RDF-based integration of physicochemical data and adverse outcome pathways for nanomaterials.Journal of cheminformatics · 2024Article
- The IDSM mass spectrometry extension: searching mass spectra using SPARQL.Bioinformatics (Oxford, England) · 2024Article
- Ontologies4Cat: investigating the landscape of ontologies for catalysis research data management.Journal of cheminformatics · 2024Article
- Chemical Species Ontology for Data Integration and Knowledge Discovery.Journal of chemical information and modeling · 2023Article
- Data Sharing in Chemistry: Lessons Learned and a Case for Mandating Structured Reaction Data.Journal of chemical information and modeling · 2023Review
- OntoPESScan: An Ontology for Potential Energy Surface Scans.ACS omega · 2023Article
- PubChem 2023 update.Nucleic acids research · 2023Article
- Unifying the identification of biomedical entities with the Bioregistry.Scientific data · 2022Article
- European Registry of Materials: global, unique identifiers for (undisclosed) nanomaterials.Journal of cheminformatics · 2022Article
- Chemical reaction network knowledge graphs: the OntoRXN ontology.Journal of cheminformatics · 2022Article
- Providing Adverse Outcome Pathways from the AOP-Wiki in a Semantic Web Format to Increase Usability and Accessibility of the Content.Applied in vitro toxicology · 2022Article
- Review
- The AOP-DB RDF: Applying FAIR Principles to the Semantic Integration of AOP Data Using the Research Description Framework.Frontiers in toxicology · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Cheminformatics is the application of informatics techniques to solve chemical problems in silico. There are many areas in biology where cheminformatics plays an important role in computational research, including metabolism, proteomics, and systems biology. One critical aspect in the application of cheminformatics in these fields is the accurate exchange of data, which is increasingly accomplished through the use of ontologies. Ontologies are formal representations of objects and their properties using a logic-based ontology language. Many such ontologies are currently being developed to represent objects across all the domains of science. Ontologies enable the definition, classification, and support for querying objects in a particular domain, enabling intelligent computer applications to be built which support the work of scientists both within the domain of interest and across interrelated neighbouring domains. Modern chemical research relies on computational techniques to filter and organise data to maximise research productivity. The objects which are manipulated in these algorithms and procedures, as well as the algorithms and procedures themselves, enjoy a kind of virtual life within computers. We will call these information entities. Here, we describe our work in developing an ontology of chemical information entities, with a primary focus on data-driven research and the integration of calculated properties (descriptors) of chemical entities within a semantic web context. Our ontology distinguishes algorithmic, or procedural information from declarative, or factual information, and renders of particular importance the annotation of provenance to calculated data. The Chemical Information Ontology is being developed as an open collaborative project. More details, together with a downloadable OWL file, are available at http://code.google.com/p/semanticchemistry/ (license: CC-BY-SA).
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Registered trials
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.