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Phenosite:一个整合小鼠表型分析平台和小鼠实验程序的网络数据库。

Phenosite: a web database integrating the mouse phenotyping platform and the experimental procedures in mice.

作者信息

Masuya Hiroshi, Yoshikawa Sumi, Heida Naohiko, Toyoda Tetsuro, Wakana Shigeharu, Shiroishi Toshihiko

机构信息

Mouse Functional Genomics Research Group, RIKEN GSC, Tsukuba, Ibaraki, Japan.

出版信息

J Bioinform Comput Biol. 2007 Dec;5(6):1173-91. doi: 10.1142/s0219720007003168.

Abstract

Recently, a number of collaborative large-scale mouse mutagenesis programs have been launched. These programs aim for a better understanding of the roles of all individual coding genes and the biological systems in which these genes participate. In international efforts to share phenotypic data among facilities/institutes, it is desirable to integrate information obtained from different phenotypic platforms reliably. Since the definitions of specific phenotypes often depend on a tacit understanding of concepts that tends to vary among different facilities, it is necessary to define phenotypes based on the explicit evidence of assay results. We have developed a website termed PhenoSITE (Phenome Semantics Information with Terminology of Experiments: http://www.gsc.riken.jp/Mouse/), in which we are trying to integrate phenotype-related information using an experimental-evidence-based approach. The site's features include (1) a baseline database for our phenotyping platform; (2) an ontology associating international phenotypic definitions with experimental terminologies used in our phenotyping platform; (3) a database for standardized operation procedures of the phenotyping platform; and (4) a database for mouse mutants using data produced from the large-scale mutagenesis program at RIKEN GSC. We have developed two types of integrated viewers to enhance the accessibility to mutant resource information. One viewer depicts a matrix view of the ontology-based classification and chromosomal location of each gene; the other depicts ontology-mediated integration of experimental protocols, baseline data, and mutant information. These approaches rely entirely upon experiment-based evidence, ensuring the reliability of the integrated data from different phenotyping platforms.

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