ArticleToxicology and applied pharmacology2017
A data-driven weighting scheme for multivariate phenotypic endpoints recapitulates zebrafish developmental cascades.
Article in Toxicology and applied pharmacology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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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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
10 citing papers in PubMed, 15 citations in OpenAlex.
- Statistical analysis of multi-endpoint phenotypic screening increases sensitivity of planarian neurotoxicity testing.Toxicological sciences : an official journal of the Society of Toxicology · 2025Article
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- Legacy and emerging per- and polyfluoroalkyl substances suppress the neutrophil respiratory burst.Journal of immunotoxicology · 2023Article
- Leveraging a High-Throughput Screening Method to Identify Mechanisms of Individual Susceptibility Differences in a Genetically Diverse Zebrafish Model.Frontiers in toxicology · 2022Article
- Development of the InTelligence And Machine LEarning (TAME) Toolkit for Introductory Data Science, Chemical-Biological Analyses, Predictive Modeling, and Database Mining for Environmental Health Research.Frontiers in toxicology · 2022Article
- Assessing the hazard of E-Cigarette flavor mixtures using zebrafish.Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association · 2020Article
- Multivariate modeling of engineered nanomaterial features associated with developmental toxicity.NanoImpact · 2019Article
- Article
- Comparative Analysis of Zebrafish and Planarian Model Systems for Developmental Neurotoxicity Screens Using an 87-Compound Library.Toxicological sciences : an official journal of the Society of Toxicology · 2019Article
- Elucidating Gene-by-Environment Interactions Associated with Differential Susceptibility to Chemical Exposure.Environmental health perspectives · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
Zebrafish have become a key alternative model for studying health effects of environmental stressors, partly due to their genetic similarity to humans, fast generation time, and the efficiency of generating high-dimensional systematic data. Studies aiming to characterize adverse health effects in zebrafish typically include several phenotypic measurements (endpoints). While there is a solid biomedical basis for capturing a comprehensive set of endpoints, making summary judgments regarding health effects requires thoughtful integration across endpoints. Here, we introduce a Bayesian method to quantify the informativeness of 17 distinct zebrafish endpoints as a data-driven weighting scheme for a multi-endpoint summary measure, called weighted Aggregate Entropy (wAggE). We implement wAggE using high-throughput screening (HTS) data from zebrafish exposed to five concentrations of all 1060 ToxCast chemicals. Our results show that our empirical weighting scheme provides better performance in terms of the Receiver Operating Characteristic (ROC) curve for identifying significant morphological effects and improves robustness over traditional curve-fitting approaches. From a biological perspective, our results suggest that developmental cascade effects triggered by chemical exposure can be recapitulated by analyzing the relationships among endpoints. Thus, wAggE offers a powerful approach for analysis of multivariate phenotypes that can reveal underlying etiological processes.
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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.