ArticleJournal of cheminformatics2014
QSAR DataBank - an approach for the digital organization and archiving of QSAR model information.
Article in Journal of cheminformatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
21 citing papers in PubMed.
- Big Data and Artificial Intelligence in Cancer Drug Discovery: Promise, Challenges, and Emerging Opportunities.Cancers · 2026Review
- Classification of Thyroid Peroxidase (TPO) Inhibitors Using Transfer Learning with SMILES Embeddings.Chemical research in toxicology · 2026Article
- Perspective on applicability of data-driven machine learning computational new approach methodologies for hazard identification in chemicals risk assessment.Journal of cheminformatics · 2026Review
- Machine Learning for Toxicity Prediction Using Chemical Structures: Pillars for Success in the Real World.Chemical research in toxicology · 2025Review
- Predictive Modeling of Pesticides Reproductive Toxicity in Earthworms Using Interpretable Machine-Learning Techniques on Imbalanced Data.ACS omega · 2025Article
- Exploring the Influence of Ionic Liquid Anion Structure on Gas-Ionic Liquid Partition Coefficients of Organic Solutes Using Machine Learning.Langmuir : the ACS journal of surfaces and colloids · 2024Article
- Data-Driven Modelling of Substituted Pyrimidine and Uracil-Based Derivatives Validated with Newly Synthesized and Antiproliferative Evaluated Compounds.International journal of molecular sciences · 2024Article
- Intrinsic Aqueous Solubility: Mechanistically Transparent Data-Driven Modeling of Drug Substances.Pharmaceutics · 2022Article
- Machine Learning Quantitative Structure-Property Relationships as a Function of Ionic Liquid Cations for the Gas-Ionic Liquid Partition Coefficient of Hydrocarbons.International journal of molecular sciences · 2022Article
- S2DV: converting SMILES to a drug vector for predicting the activity of anti-HBV small molecules.Briefings in bioinformatics · 2022Article
- Combined Naïve Bayesian, Chemical Fingerprints and Molecular Docking Classifiers to Model and Predict Androgen Receptor Binding Data for Environmentally- and Health-Sensitive Substances.International journal of molecular sciences · 2021Article
- ELIXIR and Toxicology: a community in development.F1000Research · 2021Article
- Towards reproducible computational drug discovery.Journal of cheminformatics · 2020Review
- Best Practices for QSAR Model Reporting: Physical and Chemical Properties, Ecotoxicity, Environmental Fate, Human Health, and Toxicokinetics Endpoints.Environmental health perspectives · 2018Review
- HIVprotI: an integrated web based platform for prediction and design of HIV proteins inhibitors.Journal of cheminformatics · 2018Article
- AVCpred: an integrated web server for prediction and design of antiviral compounds.Chemical biology & drug design · 2017Article
- A QSAR Study Based on SVM for the Compound of Hydroxyl Benzoic Esters.Bioinorganic chemistry and applications · 2017Article
- MetMaxStruct: A Tversky-Similarity-Based Strategy for Analysing the (Sub)Structural Similarities of Drugs and Endogenous Metabolites.Frontiers in pharmacology · 2016Article
- Many InChIs and quite some feat.Journal of computer-aided molecular design · 2015Article
- QSAR DataBank repository: open and linked qualitative and quantitative structure-activity relationship models.Journal of cheminformatics · 2015Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundResearch efforts in the field of descriptive and predictive Quantitative Structure-Activity Relationships or Quantitative Structure-Property Relationships produce around one thousand scientific publications annually. All the materials and results are mainly communicated using printed media. The printed media in its present form have obvious limitations when they come to effectively representing mathematical models, including complex and non-linear, and large bodies of associated numerical chemical data. It is not supportive of secondary information extraction or reuse efforts while in silico studies poses additional requirements for accessibility, transparency and reproducibility of the research. This gap can and should be bridged by introducing domain-specific digital data exchange standards and tools. The current publication presents a formal specification of the quantitative structure-activity relationship data organization and archival format called the QSAR DataBank (QsarDB for shorter, or QDB for shortest).
resultsThe article describes QsarDB data schema, which formalizes QSAR concepts (objects and relationships between them) and QsarDB data format, which formalizes their presentation for computer systems. The utility and benefits of QsarDB have been thoroughly tested by solving everyday QSAR and predictive modeling problems, with examples in the field of predictive toxicology, and can be applied for a wide variety of other endpoints. The work is accompanied with open source reference implementation and tools.
conclusionsThe proposed open data, open source, and open standards design is open to public and proprietary extensions on many levels. Selected use cases exemplify the benefits of the proposed QsarDB data format. General ideas for future development are discussed.
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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.