ArticleBMC pharmacology & toxicology2018
Classification and prediction of toxicity of chemicals using an automated phenotypic profiling of Caenorhabditis elegans.
Article in BMC pharmacology & toxicology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- HarnessingSensors (Basel, Switzerland) · 2025Review
- An automatic measurement method for the response of Caenorhabditis elegans to chemicals.Technology and health care : official journal of the European Society for Engineering and Medicine · 2024Article
- An automatic recognition method of nematode survival rate based on bright field and dark field experimental images.Technology and health care : official journal of the European Society for Engineering and Medicine · 2023Article
- Potent anticancer activity of a novel iridium metallodrug via oncosis.Cellular and molecular life sciences : CMLS · 2022Article
- Acute, Sublethal, and Developmental Toxicity of Kratom (International journal of environmental research and public health · 2022Article
- Article
- Chemical Class Prediction of Unknown Biomolecules Using Ion Mobility-Mass Spectrometry and Machine Learning: Supervised Inference of Feature Taxonomy from Ensemble Randomization.Analytical chemistry · 2020Article
- Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTraditional toxicological studies have relied heavily on various animal models to understand the effect of various compounds in a biological context. Considering the great cost, complexity and time involved in experiments using higher order organisms. Researchers have been exploring alternative models that avoid these disadvantages. One example of such a model is the nematode Caenorhabditis elegans. There are some advantages of C. elegans, such as small size, short life cycle, well defined genome, ease of maintenance and efficient reproduction.
methodsAs these benefits allow large scale studies to be initiated with relative ease, the problem of how to efficiently capture, organize and analyze the resulting large volumes of data must be addressed. We have developed a new method for quantitative screening of chemicals using C. elegans. 33 features were identified for each chemical treatment.
resultsThe compounds with different toxicities were shown to alter the phenotypes of C. elegans in distinct and detectable patterns. We found that phenotypic profiling revealed conserved functions to classify and predict the toxicity of different chemicals.
conclusionsOur results demonstrate the power of phenotypic profiling in C. elegans under different chemical environments.
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