Xenbase: Facilitating the Use of to Model Human Disease.

Clicks: 197
ID: 66113
2019
Article Quality & Performance Metrics
Overall Quality
0.0 /100
Combines engagement data with AI-assessed academic quality
AI Quality Assessment
Not analyzed
At a fundamental level most genes, signaling pathways, biological functions and organ systems are highly conserved between man and all vertebrate species. Leveraging this conservation, researchers are increasingly using the experimental advantages of the amphibian to model human disease. The online resource, Xenbase, enables human disease modeling by curating the literature published in PubMed and integrating these data with orthologous human genes, anatomy, and more recently with links to the Online Mendelian Inheritance in Man resource (OMIM) and the Human Disease Ontology (DO). Here we review how Xenbase supports disease modeling and report on a meta-analysis of the published research providing an overview of the different types of diseases being modeled in and the variety of experimental approaches being used. Text mining of over 50,000 research articles imported into Xenbase from PubMed identified approximately 1,000 putative disease- modeling articles. These articles were manually assessed and annotated with disease ontologies, which were then used to classify papers based on disease type. We found that is being used to study a diverse array of disease with three main experimental approaches: cell-free egg extracts to study fundamental aspects of cellular and molecular biology, oocytes to study ion transport and channel physiology and embryo experiments focused on congenital diseases. We integrated these data into Xenbase Disease Pages to allow easy navigation to disease information on external databases. Results of this analysis will equip researchers with a suite of experimental approaches available to model or dissect a pathological process. Ideally clinicians and basic researchers will use this information to foster collaborations necessary to interrogate the development and treatment of human diseases.
Reference Key
nenni2019xenbasefrontiers Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Nenni, Mardi J;Fisher, Malcolm E;James-Zorn, Christina;Pells, Troy J;Ponferrada, Virgilio;Chu, Stanley;Fortriede, Joshua D;Burns, Kevin A;Wang, Ying;Lotay, Vaneet S;Wang, Dong Zhou;Segerdell, Erik;Chaturvedi, Praneet;Karimi, Kamran;Vize, Peter D;Zorn, Aaron M;
Journal Frontiers in physiology
Year 2019
DOI 10.3389/fphys.2019.00154
URL
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.