ZFIN updates to support zebrafish environmental exposure data

The Zebrafish Information Network (ZFIN, zfin.org) is the database resource for genetic, genomic, and phenotypic data from research using zebrafish, Danio rerio. ZFIN curates information about genetic perturbations, gene expression, phenotype, gene function, and human disease models from zebrafish research publications and makes these data available to researchers worldwide. Over the past 20 years, zebrafish have increasingly been used to investigate the effects of environmental exposures, becoming an ideal model to study toxicity, phenotypic outcomes, and gene-chemical interactions. Despite this, database resources supporting zebrafish toxicology and environmental exposure research are limited. To fill this gap, ZFIN has expanded functionality to incorporate and convey toxicology data better. ZFIN annotations for gene expression, phenotype, and human disease models include information about genotypes and experimental conditions used. One type of experimental condition the database captures is the application of chemicals to zebrafish. ZFIN annotates chemicals using the Chemical Entities of Biological Interest Ontology (ChEBI) along with the Zebrafish Experimental Conditions Ontology (ZECO) to denote route of exposure and other experimental conditions. These features allow researchers to search phenotypes and human disease models linked to chemicals more efficiently. Here, we discuss how experimental conditions are displayed on ZFIN web pages, the data displayed on chemical term pages, and how to search and download data associated with chemical exposure experiments.

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Publication Details

Journal
Genetics
Published
2025-02-04
DOI
https://doi.org/10.1093/genetics/iyaf021
Citations
3
Primary Topic
Biomedical Text Mining and Ontologies
Type
article
Field-Weighted Citation Impact
2.42

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article

ZFIN updates to support zebrafish environmental exposure data

Wei-Chia Tseng, Holly Paddock, Amy Singer, Yvonne M. Bradford et al.
3 citations
Genetics
Biomedical Text Mining and Ontologies
2.42
article

ZFIN updates to support zebrafish environmental exposure data

Wei-Chia Tseng, Holly Paddock, Amy Singer, Yvonne M. Bradford, Ceri E. Van Slyke, Jonathan B. Muyskens, Sridhar Ramachandran, Christian Pich, Monte Westerfield, Ryan Taylor, David Fashena, Leyla Ruzicka, Douglas G. Howe, Ryan Martin
article en
3 citations

Abstract

The Zebrafish Information Network (ZFIN, zfin.org) is the database resource for genetic, genomic, and phenotypic data from research using zebrafish, Danio rerio. ZFIN curates information about genetic perturbations, gene expression, phenotype, gene function, and human disease models from zebrafish research publications and makes these data available to researchers worldwide. Over the past 20 years, zebrafish have increasingly been used to investigate the effects of environmental exposures, becoming an ideal model to study toxicity, phenotypic outcomes, and gene-chemical interactions. Despite this, database resources supporting zebrafish toxicology and environmental exposure research are limited. To fill this gap, ZFIN has expanded functionality to incorporate and convey toxicology data better. ZFIN annotations for gene expression, phenotype, and human disease models include information about genotypes and experimental conditions used. One type of experimental condition the database captures is the application of chemicals to zebrafish. ZFIN annotates chemicals using the Chemical Entities of Biological Interest Ontology (ChEBI) along with the Zebrafish Experimental Conditions Ontology (ZECO) to denote route of exposure and other experimental conditions. These features allow researchers to search phenotypes and human disease models linked to chemicals more efficiently. Here, we discuss how experimental conditions are displayed on ZFIN web pages, the data displayed on chemical term pages, and how to search and download data associated with chemical exposure experiments.

GeneticsVol. 229(3)
University of Oregon (US)
National Institutes of Health
Life below water
Openalex Percentile: Top 13%
Biomedical Text Mining and Ontologies
2.42
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