ArticleEnvironmental and molecular mutagenesis2014
Emerging approaches in predictive toxicology.
Article in Environmental and molecular mutagenesis, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed, 36 citations in OpenAlex.
- Article
- ProTox 3.0: a webserver for the prediction of toxicity of chemicals.Nucleic acids research · 2024Article
- In silico toxicity and immunological interactions of components of calcium silicate-based and epoxy resin-based endodontic sealers.Clinical oral investigations · 2024Article
- Large-Scale Modeling of Multispecies Acute Toxicity End Points Using Consensus of Multitask Deep Learning Methods.Journal of chemical information and modeling · 2021Article
- Evaluation of Pb concentrations in selected vegetables and portable drinking water, and intelligent quotients of school children in Ishiagu-a Pb mining community: health risk assessment using predictive modelling.Environmental monitoring and assessment · 2020Article
- ProTox-II: a webserver for the prediction of toxicity of chemicals.Nucleic acids research · 2018Article
- A New Chapter for Mesenchymal Stem Cells: Decellularized Extracellular Matrices.Stem cell reviews and reports · 2017Review
- The Next Generation of Risk Assessment Multi-Year Study-Highlights of Findings, Applications to Risk Assessment, and Future Directions.Environmental health perspectives · 2016Review
- Identification of Genes That Modulate Susceptibility to Formaldehyde and Imatinib by Functional Genomic Screening in Human Haploid KBM7 Cells.Toxicological sciences : an official journal of the Society of Toxicology · 2016Article
- Intersection of toxicogenomics and high throughput screening in the Tox21 program: an NIEHS perspective.International journal of biotechnologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 8 institutions in 1 country.
Funding
Abstract
Predictive toxicology plays an important role in the assessment of toxicity of chemicals and the drug development process. While there are several well-established in vitro and in vivo assays that are suitable for predictive toxicology, recent advances in high-throughput analytical technologies and model systems are expected to have a major impact on the field of predictive toxicology. This commentary provides an overview of the state of the current science and a brief discussion on future perspectives for the field of predictive toxicology for human toxicity. Computational models for predictive toxicology, needs for further refinement and obstacles to expand computational models to include additional classes of chemical compounds are highlighted. Functional and comparative genomics approaches in predictive toxicology are discussed with an emphasis on successful utilization of recently developed model systems for high-throughput analysis. The advantages of three-dimensional model systems and stem cells and their use in predictive toxicology testing are also described.
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.