ReviewMolecular omics2018
Developments in toxicogenomics: understanding and predicting compound-induced toxicity from gene expression data.
Review in Molecular omics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 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
51 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic Review of Multi-Omics Approaches to Investigate Toxicological Effects in Macrophages.International journal of molecular sciences · 2020Pooled it
- Epidemiological and bioinformatics analyses of air pollution and genetic susceptibility in aortic stenosis risk.Nature communications · 2026Article
- Single-cell transcriptomics reveals a differential response of human bronchial epithelial cell-types to cadmium chloride.Archives of toxicology · 2026Article
- Physiologically relevant 3D CRISPR screening enhances mechanistic insight into chemical toxicity compared to 2D screening.Toxicology · 2026Article
- Physiologically Relevant 3D CRISPR Screening Enhances Mechanistic Insight into Chemical Toxicity Compared to 2D Screening.bioRxiv : the preprint server for biology · 2025Article
- ToxAssay: a hierarchical model-driven tool for advanced toxicogenomics biomarker discovery.Bioinformatics (Oxford, England) · 2025Article
- Discovering a predictive metabolic signature of drug-induced structural cardiotoxicity in cardiac microtissues.Archives of toxicology · 2025Article
- Utilizing rat kidney gene co-expression networks to enhance safety assessment biomarker identification and human translation.iScience · 2025Article
- Investigating the Use of Diagnostic Genes in Integrated Monitoring with a Laboratory and Field Study on Flounder (Toxics · 2025Article
- Establishment of interpretable cytotoxicity prediction models using machine learning analysis of transcriptome features.Acta pharmaceutica Sinica. B · 2025Article
- Progress in toxicogenomics to protect human health.Nature reviews. Genetics · 2025Review
- Bridging organ transcriptomics for advancing multiple organ toxicity assessment with a generative AI approach.NPJ digital medicine · 2024Article
- Computational Strategies for Assessing Adverse Outcome Pathways: Hepatic Steatosis as a Case Study.International journal of molecular sciences · 2024Review
- A Network Toxicology Approach for Mechanistic Modelling of Nanomaterial Hazard and Adverse Outcomes.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Probing Liver Injuries Induced by Thioacetamide in Human In Vitro Pooled Hepatocyte Experiments.International journal of molecular sciences · 2024Article
- Using Transcriptomics and Cell Morphology Data in Drug Discovery: The Long Road to Practice.ACS medicinal chemistry letters · 2023Review
- Identifying multiscale translational safety biomarkers using a network-based systems approach.iScience · 2023Article
- Systems bioengineering approaches for developmental toxicology.Computational and structural biotechnology journal · 2023Review
- Daphnia as a model organism to probe biological responses to nanomaterials-from individual to population effects via adverse outcome pathways.Frontiers in toxicology · 2023Review
- Analyses of Transcriptomics Cell Signalling for Pre-Screening Applications in the Integrated Approach for Testing and Assessment of Non-Genotoxic Carcinogens.International journal of molecular sciences · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
The toxicogenomics field aims to understand and predict toxicity by using 'omics' data in order to study systems-level responses to compound treatments. In recent years there has been a rapid increase in publicly available toxicological and 'omics' data, particularly gene expression data, and a corresponding development of methods for its analysis. In this review, we summarize recent progress relating to the analysis of RNA-Seq and microarray data, review relevant databases, and highlight recent applications of toxicogenomics data for understanding and predicting compound toxicity. These include the analysis of differentially expressed genes and their enrichment, signature matching, methods based on interaction networks, and the analysis of co-expression networks. In the future, these state-of-the-art methods will likely be combined with new technologies, such as whole human body models, to produce a comprehensive systems-level understanding of toxicity that reduces the necessity of in vivo toxicity assessment in animal models.
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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.