ReviewEnvironmental health perspectives2004
Toxicogenomics in risk assessment: an overview of an HESI collaborative research program.
Review in Environmental health perspectives, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 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
29 citing papers in PubMed, 1 synthesis or guideline pooled it.
- 'Omics in environmental epidemiological studies of chemical exposures: A systematic evidence map.Environment international · 2022Pooled it
- Multidimensional assessment of the biological effects of electronic cigarettes on lung bronchial epithelial cells.Scientific reports · 2024Article
- Pyrrolizidine alkaloids cause cell cycle and DNA damage repair defects as analyzed by transcriptomics in cytochrome P450 3A4-overexpressing HepG2 clone 9 cells.Cell biology and toxicology · 2022Article
- Drivers of and Obstacles to the Adoption of Toxicogenomics for Chemical Risk Assessment: Insights from Social Science Perspectives.Environmental health perspectives · 2020Article
- The use of evidence from high-throughput screening and transcriptomic data in human health risk assessments.Toxicology and applied pharmacology · 2019Article
- Narrowing the Gap BetweenFrontiers in pharmacology · 2019Article
- Technical guide for applications of gene expression profiling in human health risk assessment of environmental chemicals.Regulatory toxicology and pharmacology : RTP · 2015Article
- Article
- DNA microarray-based gene expression profiling of estrogenic chemicals.Cellular and molecular life sciences : CMLS · 2014Review
- Incorporating epigenetic data into the risk assessment process for the toxic metals arsenic, cadmium, chromium, lead, and mercury: strategies and challenges.Frontiers in genetics · 2014Review
- Oligonucleotide microarray analysis of dietary-induced hyperlipidemia gene expression profiles in miniature pigs.PloS one · 2012Article
- Oligonucleotide microarray analysis of age-related gene expression profiles in miniature pigs.PloS one · 2011Article
- Successful drug development despite adverse preclinical findings part 2: examples.Journal of toxicologic pathology · 2010Article
- A new method for the evaluation of vaccine safety based on comprehensive gene expression analysis.Journal of biomedicine & biotechnology · 2010Review
- Inter-laboratory reproducibility of fast gas chromatography-electron impact-time of flight mass spectrometry (GC-EI-TOF/MS) based plant metabolomics.Metabolomics : Official journal of the Metabolomic Society · 2009Article
- Characterization and interlaboratory comparison of a gene expression signature for differentiating genotoxic mechanisms.Toxicological sciences : an official journal of the Society of Toxicology · 2009Article
- Sources of variation in baseline gene expression levels from toxicogenomics study control animals across multiple laboratories.BMC genomics · 2008Article
- Article
- Workgroup report: Review of genomics data based on experience with mock submissions--view of the CDER Pharmacology Toxicology Nonclinical Pharmacogenomics Subcommittee.Environmental health perspectives · 2006Review
- Recent applications of DNA microarray technology to toxicology and ecotoxicology.Environmental health perspectives · 2006Review
Corrections and comments
- Commented on by
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The value of genomic approaches in hypothesis generation is being realized as a tool for understanding toxicity and consequently contributing to an assessment of drug and chemical safety. In 1999 the membership of the International Life Sciences Institute Health and Environmental Sciences Institute formed a committee to develop a collaborative scientific program to address issues, challenges, and opportunities afforded by the emerging field of toxicogenomics. Experts and advisors from academia and government laboratories participate on the committee, along with approximately 30 corporate member organizations from the pharmaceutical, agrochemical, chemical, and consumer products industries. The committee has designed, conducted, and analyzed numerous toxicogenomic experiments within the broad fields of hepatotoxicity, nephrotoxicity, and genotoxicity. The considerable body of data generated by these programs has been instrumental in increasing understanding of sources of biological and technical variability in the alignment of toxicant-induced transcription changes with the accepted mechanism of action of these agents and the challenges in the consistent analysis and sharing of the voluminous data sets generated by these approaches. Recognizing the importance of standardized microarray data formats and public repository databases as the mechanism by which microarray data can be compared and interpreted by the scientific community, the committee has partnered with the European Bioinformatics Institute to develop a database to house the data generated by its collaborative research.
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.