ArticleScientific reports2015
An automated fitting procedure and software for dose-response curves with multiphasic features.
Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 papers, 1 of them a synthesis that pooled it.
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Who cites it
79 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- Identification of therapeutic targets for renal medullary carcinoma via integrated genomic and transcriptomic profiling.Cell reports. Medicine · 2025Article
- Detrended fluctuation analysis of heart rate variability during exercise: Time to reconsider the theoretical and methodological background. Comment on: Cassirame et al.`s (2025) Detrended fluctuation analysis to determine physiologic thresholds, investigation and evidence from incremental cycling test. Eur J Appl Physiol 125:523-533.European journal of applied physiology · 2025Article
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- Translational modeling-based evidence for enhanced efficacy of standard-of-care drugs in combination with anti-microRNA-155 in non-small-cell lung cancer.Molecular cancer · 2024Article
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- Experimental and data analysis advances in thermal proteome profiling.Cell reports methods · 2024Review
19 more citing papers are in PubMed but not listed here.
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Authors and funding
8 authors.
Funding
Abstract
In cancer pharmacology (and many other areas), most dose-response curves are satisfactorily described by a classical Hill equation (i.e. 4 parameters logistical). Nevertheless, there are instances where the marked presence of more than one point of inflection, or the presence of combined agonist and antagonist effects, prevents straight-forward modelling of the data via a standard Hill equation. Here we propose a modified model and automated fitting procedure to describe dose-response curves with multiphasic features. The resulting general model enables interpreting each phase of the dose-response as an independent dose-dependent process. We developed an algorithm which automatically generates and ranks dose-response models with varying degrees of multiphasic features. The algorithm was implemented in new freely available Dr Fit software (sourceforge.net/projects/drfit/). We show how our approach is successful in describing dose-response curves with multiphasic features. Additionally, we analysed a large cancer cell viability screen involving 11650 dose-response curves. Based on our algorithm, we found that 28% of cases were better described by a multiphasic model than by the Hill model. We thus provide a robust approach to fit dose-response curves with various degrees of complexity, which, together with the provided software implementation, should enable a wide audience to easily process their own data.
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