ArticleWellcome open research2016
Hierarchical Bayesian inference for ion channel screening dose-response data.
Article in Wellcome open research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed, 30 citations in OpenAlex.
- BiDRA: Bayesian inference as a robust alternative to non-linear regression for dose-response efficiency metrics assessment.Bioinformatics advances · 2026Article
- Computational modelling for improved translation of cardiac inotropic and lusitropic drug effects from rats to humans.Journal of pharmacological and toxicological methods · 2025Article
- Sensitivity Analysis of the Inputs for Bioactivity-Exposure Ratio Calculations in a NAM-Based Systemic Safety Toolbox.NAM journal · 2025Article
- The Current State of Realistic Heart Models for Disease Modelling and Cardiotoxicity.International journal of molecular sciences · 2024Review
- Inclusion of Control Data in Fits to Concentration-Response Curves Improves Estimates of Half-Maximal Concentrations.Journal of medicinal chemistry · 2023Article
- Beyond AOPs: A Mechanistic Evaluation of NAMs in DART Testing.Frontiers in toxicology · 2022Article
- Use of Patient Health Records to Quantify Drug-Related Pro-arrhythmic Risk.Cell reports. Medicine · 2020Article
- A systematic strategy for estimating hERG block potency and its implications in a new cardiac safety paradigm.Toxicology and applied pharmacology · 2020Article
- Classifying Drugs by their Arrhythmogenic Risk Using Machine Learning.Biophysical journal · 2020Article
- General Principles for the Validation of Proarrhythmia Risk Prediction Models: An Extension of the CiPA In Silico Strategy.Clinical pharmacology and therapeutics · 2020Article
- Four Ways to Fit an Ion Channel Model.Biophysical journal · 2019Article
- Enhancing the drug discovery process: Bayesian inference for the analysis and comparison of dose-response experiments.Bioinformatics (Oxford, England) · 2019Article
- Machine learning in drug development: Characterizing the effect of 30 drugs on the QT interval using Gaussian process regression, sensitivity analysis, and uncertainty quantification.Computer methods in applied mechanics and engineering · 2019Article
- Global Sensitivity Analysis of Ventricular Myocyte Model-Derived Metrics for Proarrhythmic Risk Assessment.Frontiers in pharmacology · 2019Article
- Reproducible model development in the cardiac electrophysiology Web Lab.Progress in biophysics and molecular biology · 2018Article
- Defining informative priors for ensemble modeling in systems biology.Nature protocols · 2018Article
- Tailoring Mathematical Models to Stem-Cell Derived Cardiomyocyte Lines Can Improve Predictions of Drug-Induced Changes to Their Electrophysiology.Frontiers in physiology · 2017Article
- Uncertainty Quantification Reveals the Importance of Data Variability and Experimental Design Considerations forFrontiers in physiology · 2017Article
- Novel Two-Step Classifier for Torsades de Pointes Risk Stratification from Direct Features.Frontiers in pharmacology · 2017Article
- Quantitative Comparison of Effects of Dofetilide, Sotalol, Quinidine, and Verapamil between HumanFrontiers in physiology · 2017Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 3 countries.
Funding
Abstract
Dose-response (or 'concentration-effect') relationships commonly occur in biological and pharmacological systems and are well characterised by Hill curves. These curves are described by an equation with two parameters: the inhibitory concentration 50% (IC50); and the Hill coefficient. Typically just the 'best fit' parameter values are reported in the literature. Here we introduce a Python-based software tool,
Indexed as
Identifiers
What OpenQuestion holds
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.