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Nucleic Acids Res 2022 Jan 07;50D1:D970-D979. doi: 10.1093/nar/gkab1005.
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Echinobase: leveraging an extant model organism database to build a knowledgebase supporting research on the genomics and biology of echinoderms.

Arshinoff BI , Cary GA , Karimi K , Foley S , Agalakov S , Delgado F , Lotay VS , Ku CJ , Pells TJ , Beatman TR , Kim E , Cameron RA , Vize PD , Telmer CA , Croce JC , Ettensohn CA , Hinman VF .

Echinobase ( is a third generation web resource supporting genomic research on echinoderms. The new version was built by cloning the mature Xenopus model organism knowledgebase, Xenbase, refactoring data ingestion pipelines and modifying the user interface to adapt to multispecies echinoderm content. This approach leveraged over 15 years of previous database and web application development to generate a new fully featured informatics resource in a single year. In addition to the software stack, Echinobase uses the private cloud and physical hosts that support Xenbase. Echinobase currently supports six echinoderm species, focused on those used for genomics, developmental biology and gene regulatory network analyses. Over 38 000 gene pages, 18 000 publications, new improved genome assemblies, JBrowse genome browser and BLAST + services are available and supported by the development of a new echinoderm anatomical ontology, uniformly applied formal gene nomenclature, and consistent orthology predictions. A novel feature of Echinobase is integrating support for multiple, disparate species. New genomes from the diverse echinoderm phylum will be added and supported as data becomes available. The common code development design of the integrated knowledgebases ensures parallel improvements as each resource evolves. This approach is widely applicable for developing new model organism informatics resources.

PubMed ID: 34791383
PMC ID: PMC8728261
Article link: Nucleic Acids Res
Grant support: [+]

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References [+] :
Alliance of Genome Resources Consortium, The Alliance of Genome Resources: Building a Modern Data Ecosystem for Model Organism Databases. 2019, Pubmed