ArticleDatabase : the journal of biological databases and curation2019
Quantitative phenotype analysis to identify, validate and compare rat disease models.
Article in Database : the journal of biological databases and curation, 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
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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.
- 2022 updates to the Rat Genome Database: a Findable, Accessible, Interoperable, and Reusable (FAIR) resource.Genetics · 2023Article
- Genome-to-phenome research in rats: progress and perspectives.International journal of biological sciences · 2021Review
- The Year of the Rat: The Rat Genome Database at 20: a multi-species knowledgebase and analysis platform.Nucleic acids research · 2020Article
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
Abstract
The laboratory rat has been widely used as an animal model in biomedical research. There are many strains exhibiting a wide variety of phenotypes. Capturing these phenotypes in a centralized database provides researchers with an easy method for choosing the appropriate strains for their studies. Existing resources have provided some preliminary work in rat phenotype databases. However, existing resources suffer from problems such as small number of animals, lack of updating, web interface queries limitations and lack of standardized metadata. The Rat Genome Database (RGD) PhenoMiner tool has provided the first step in this effort by standardizing and integrating data from individual studies. Our work, mainly utilizing data curated in RGD, involves the following key steps: (i) we developed a meta-analysis pipeline to automatically integrate data from heterogeneous sources and to produce expected ranges (standardized phenotype ranges) for different strains and phenotypes under different experimental conditions; (ii) we created tools to visualize expected ranges for individual strains and strain groups. We developed a meta-analysis pipeline and an interactive web interface that summarizes and visualizes expected ranges produced from the meta-analysis pipeline. Automation of the pipeline allows for updates as additional data becomes available. The interactive web interface provides curators and researchers with a platform for identifying and validating expected ranges for a variety of quantitative phenotypes. The data analysis result and visualization tools will promote an understanding of rat disease models, guide researchers to choose optimal strains for their research needs and encourage data sharing from different research hubs. Such resources also help to promote research reproducibility. The interactive platforms created in this project will continue to provide a valuable resource for translational research efforts.
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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.