ArticleJournal of computer-aided molecular design2015
Activity, assay and target data curation and quality in the ChEMBL database.
Article in Journal of computer-aided molecular design, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 75 papers.
What it found
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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
75 citing papers in PubMed.
- Pharmacological stratification of public bioactivity databases: a reusable, OECD-anchored curation and benchmarking framework demonstrated for opioid receptors.Digital discovery · 2026Article
- Identification of YES1 Inhibitors From Approved Drugs Using a Multimodal Deep Learning Framework.Molecular informatics · 2026Article
- PAD4-DB: A Curated Structure-Activity Resource Reveals Hub-Organized Activity Cliffs and Scaffold-Dependent SAR Ruggedness in PAD4 Inhibitors.International journal of molecular sciences · 2026Article
- Centralized Review of Alzheimer's Disease and Related Dementias Biomedical Repositories and Computational Methods.Bioengineering (Basel, Switzerland) · 2026Review
- Defining the Data set Defines the QSAR Claim.Journal of chemical information and modeling · 2026Article
- Bridging genomics and pharmacoepidemiology to expand treatment options for alcohol use disorder.Alcohol, clinical & experimental research · 2026Article
- Review
- Integrating artificial intelligence and manual curation to enhance bioassay annotations in ChEMBL.Journal of cheminformatics · 2026Article
- Bridging Genomics and Pharmacoepidemiology to Expand Treatment Options for Alcohol Use Disorder.medRxiv : the preprint server for health sciences · 2026Article
- Computer-Aided Discovery of Drugs Against Chagas Disease.Methods in molecular biology (Clifton, N.J.) · 2026Article
- ProfhEX: Empowering Early Drug Discovery with Machine Learning-Based Target Profiling and Liability Prediction.Journal of chemical information and modeling · 2025Article
- A Benchmark Set of Bioactive Molecules for Diversity Analysis of Compound Libraries and Combinatorial Chemical Spaces.Journal of chemical information and modeling · 2025Article
- Artificial Intelligence in Molecular Optimization: Current Paradigms and Future Frontiers.International journal of molecular sciences · 2025Review
- Data Exploration for Target Predictions Using Proprietary and Publicly Available Data Sets.Chemical research in toxicology · 2025Article
- MHNfs: Prompting In-Context Bioactivity Predictions for Low-Data Drug Discovery.Journal of chemical information and modeling · 2025Article
- Integrating pharmacogenomics and cheminformatics with diverse disease phenotypes for cell type-guided drug discovery.Genome medicine · 2025Article
- The Present State and Potential Applications of Artificial Intelligence in Cancer Diagnosis and Treatment.Recent patents on anti-cancer drug discovery · 2025Review
- Combining crystallographic and binding affinity data towards a novel dataset of small molecule overlays.Journal of computer-aided molecular design · 2024Article
- Advancing Drug Safety in Drug Development: Bridging Computational Predictions for Enhanced Toxicity Prediction.Chemical research in toxicology · 2024Review
- Binding Curve Viewer: Visualizing the Equilibrium and Kinetics of Protein-Ligand Binding and Competitive Binding.Journal of chemical information and modeling · 2024Article
15 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
The emergence of a number of publicly available bioactivity databases, such as ChEMBL, PubChem BioAssay and BindingDB, has raised awareness about the topics of data curation, quality and integrity. Here we provide an overview and discussion of the current and future approaches to activity, assay and target data curation of the ChEMBL database. This curation process involves several manual and automated steps and aims to: (1) maximise data accessibility and comparability; (2) improve data integrity and flag outliers, ambiguities and potential errors; and (3) add further curated annotations and mappings thus increasing the usefulness and accuracy of the ChEMBL data for all users and modellers in particular. Issues related to activity, assay and target data curation and integrity along with their potential impact for users of the data are discussed, alongside robust selection and filter strategies in order to avoid or minimise these, depending on the desired application.
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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.