ArticleMolecules (Basel, Switzerland)2019
Improving the Utility of the Tox21 Dataset by Deep Metadata Annotations and Constructing Reusable Benchmarked Chemical Reference Signatures.
Article in Molecules (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- An integrated chemical environment with tools for chemical safety testing.Toxicology in vitro : an international journal published in association with BIBRA · 2020Article
- LINCS Data Portal 2.0: next generation access point for perturbation-response signatures.Nucleic acids research · 2020Article
- DeepSnap-Deep Learning Approach Predicts Progesterone Receptor Antagonist Activity With High Performance.Frontiers in bioengineering and biotechnology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
The Toxicology in the 21st Century (Tox21) project seeks to develop and test methods for high-throughput examination of the effect certain chemical compounds have on biological systems. Although primary and toxicity assay data were readily available for multiple reporter gene modified cell lines, extensive annotation and curation was required to improve these datasets with respect to how FAIR (Findable, Accessible, Interoperable, and Reusable) they are. In this study, we fully annotated the Tox21 published data with relevant and accepted controlled vocabularies. After removing unreliable data points, we aggregated the results and created three sets of signatures reflecting activity in the reporter gene assays, cytotoxicity, and selective reporter gene activity, respectively. We benchmarked these signatures using the chemical structures of the tested compounds and obtained generally high receiver operating characteristic (ROC) scores, suggesting good quality and utility of these signatures and the underlying data. We analyzed the results to identify promiscuous individual compounds and chemotypes for the three signature categories and interpreted the results to illustrate the utility and re-usability of the datasets. With this study, we aimed to demonstrate the importance of data standards in reporting screening results and high-quality annotations to enable re-use and interpretation of these data. To improve the data with respect to all FAIR criteria, all assay annotations, cleaned and aggregate datasets, and signatures were made available as standardized dataset packages (Aggregated Tox21 bioactivity data, 2019).
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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.