文章基本信息

标题：Establishment and application of information resource of mutant mice in RIKEN BioResource Research Center
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作者：Hiroshi Masuya ; Daiki Usuda ; Hatsumi Nakata 等
期刊名称：Laboratory Animal Research
印刷版ISSN：1738-6055
电子版ISSN：2233-7660
出版年度：2021
卷号：37
期号：1
页码：1-11
DOI：10.1186/s42826-020-00068-8
语种：English
出版社：BioMed Central Ltd.
摘要：Online databases are crucial infrastructures to facilitate the wide effective and efficient use of mouse mutant resources in life sciences. The number and types of mouse resources have been rapidly growing due to the development of genetic modification technology with associated information of genomic sequence and phenotypes. Therefore, data integration technologies to improve the findability, accessibility, interoperability, and reusability of mouse strain data becomes essential for mouse strain repositories. In 2020, the RIKEN BioResource Research Center released an integrated database of bioresources including, experimental mouse strains, Arabidopsis thaliana as a laboratory plant, cell lines, microorganisms, and genetic materials using Resource Description Framework-related technologies. The integrated database shows multiple advanced features for the dissemination of bioresource information. The current version of our online catalog of mouse strains which functions as a part of the integrated database of bioresources is available from search bars on the page of the Center ( https://brc.riken.jp ) and the Experimental Animal Division ( https://mus.brc.riken.jp/ ) websites. The BioResource Research Center also released a genomic variation database of mouse strains established in Japan and Western Europe, MoG+ ( https://molossinus.brc.riken.jp/mogplus/ ), and a database for phenotype-phenotype associations across the mouse phenome using data from the International Mouse Phenotyping Platform. In this review, we describe features of current version of databases related to mouse strain resources in RIKEN BioResource Research Center and discuss future views.
关键词：Bioresource;Mouse mutation information resource;Database;data integration;Semantic web;Ontology