ArticleNucleic acids research2017
CEBS: a comprehensive annotated database of toxicological data.
Article in Nucleic acids research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.
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
34 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Computational resources associating diseases with genotypes, phenotypes and exposures.Briefings in bioinformatics · 2019Pooled it
- Navigating through toxicological data: review of toxicological databases and sources in the interdisciplinary context including-chemicals, cosmetics, pharmaceuticals and forensics.Archives of toxicology · 2026Review
- Comparative Genomic Hybridization (CGH) in Genotoxicology: From the Basics to Modern Approaches.Methods in molecular biology (Clifton, N.J.) · 2026Review
- ToxAssay: a hierarchical model-driven tool for advanced toxicogenomics biomarker discovery.Bioinformatics (Oxford, England) · 2025Article
- Progress in toxicogenomics to protect human health.Nature reviews. Genetics · 2025Review
- Unlocking the potential of AI: Machine learning and deep learning models for predicting carcinogenicity of chemicals.Journal of environmental science and health. Part C, Toxicology and carcinogenesis · 2025Review
- Standardizing Extracted Data Using Automated Application of Controlled Vocabularies.Environmental health perspectives · 2024Article
- Artificial intelligence integration in the drug lifecycle and in regulatory science: policy implications, challenges and opportunities.Frontiers in pharmacology · 2024Article
- The Environmental Conditions, Treatments, and Exposures Ontology (ECTO): connecting toxicology and exposure to human health and beyond.Journal of biomedical semantics · 2023Article
- Short-term in vivo testing to discriminate genotoxic carcinogens from non-genotoxic carcinogens and non-carcinogens using next-generation RNA sequencing, DNA microarray, and qPCR.Genes and environment : the official journal of the Japanese Environmental Mutagen Society · 2023Review
- TOXRIC: a comprehensive database of toxicological data and benchmarks.Nucleic acids research · 2023Article
- Using Prior Toxicological Data to Support Dose-Response Assessment─Identifying Plausible Prior Distributions for Dichotomous Dose-Response Models.Environmental science & technology · 2022Article
- Machine Learning and Artificial Intelligence in Toxicological Sciences.Toxicological sciences : an official journal of the Society of Toxicology · 2022Review
- Continuous Model Averaging for Benchmark Dose Analysis: Averaging Over Distributional Forms.Environmetrics · 2022Article
- Statistical Analysis of Rodent Body Weight Data is Robust to Departures from Normality in Historical National Toxicology Program Studies Dated 1980-2013.Journal of young investigators · 2022Article
- CEBS update: curated toxicology database with enhanced tools for data integration.Nucleic acids research · 2022Article
- Emerging Bioinformatics Methods and Resources in Drug Toxicology.Methods in molecular biology (Clifton, N.J.) · 2022Article
- In Silico Methods for Chromosome Damage.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Essential oil fromBulletin of the National Research Centre · 2022Article
- Review
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The Chemical Effects in Biological Systems database (CEBS) is a comprehensive and unique toxicology resource that compiles individual and summary animal data from the National Toxicology Program (NTP) testing program and other depositors into a single electronic repository. CEBS has undergone significant updates in recent years and currently contains over 11 000 test articles (exposure agents) and over 8000 studies including all available NTP carcinogenicity, short-term toxicity and genetic toxicity studies. Study data provided to CEBS are manually curated, accessioned and subject to quality assurance review prior to release to ensure high quality. The CEBS database has two main components: data collection and data delivery. To accommodate the breadth of data produced by NTP, the CEBS data collection component is an integrated relational design that allows the flexibility to capture any type of electronic data (to date). The data delivery component of the database comprises a series of dedicated user interface tables containing pre-processed data that support each component of the user interface. The user interface has been updated to include a series of nine Guided Search tools that allow access to NTP summary and conclusion data and larger non-NTP datasets. The CEBS database can be accessed online at http://www.niehs.nih.gov/research/resources/databases/cebs/.
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.