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MAGIC数据库与界面:用于基因发现与表达的集成软件包。

MAGIC database and interfaces: an integrated package for gene discovery and expression.

作者信息

Cordonnier-Pratt Marie-Michèle, Liang Chun, Wang Haiming, Kolychev Dmitri S, Sun Feng, Freeman Robert, Sullivan Robert, Pratt Lee H

机构信息

Department of Plant Biology, University of Georgia, Athens, GA 30602, USA.

出版信息

Comp Funct Genomics. 2004;5(3):268-75. doi: 10.1002/cfg.399.

Abstract

The rapidly increasing rate at which biological data is being produced requires a corresponding growth in relational databases and associated tools that can help laboratories contend with that data. With this need in mind, we describe here a Modular Approach to a Genomic, Integrated and Comprehensive (MAGIC) Database. This Oracle 9i database derives from an initial focus in our laboratory on gene discovery via production and analysis of expressed sequence tags (ESTs), and subsequently on gene expression as assessed by both EST clustering and microarrays. The MAGIC Gene Discovery portion of the database focuses on information derived from DNA sequences and on its biological relevance. In addition to MAGIC SEQ-LIMS, which is designed to support activities in the laboratory, it contains several additional subschemas. The latter include MAGIC Admin for database administration, MAGIC Sequence for sequence processing as well as sequence and clone attributes, MAGIC Cluster for the results of EST clustering, MAGIC Polymorphism in support of microsatellite and single-nucleotide-polymorphism discovery, and MAGIC Annotation for electronic annotation by BLAST and BLAT. The MAGIC Microarray portion is a MIAME-compliant database with two components at present. These are MAGIC Array-LIMS, which makes possible remote entry of all information into the database, and MAGIC Array Analysis, which provides data mining and visualization. Because all aspects of interaction with the MAGIC Database are via a web browser, it is ideally suited not only for individual research laboratories but also for core facilities that serve clients at any distance.

摘要

生物数据的快速增长速度要求关系数据库及相关工具相应增加,以帮助实验室处理这些数据。考虑到这一需求,我们在此描述一种基因组、集成且全面的模块化方法(MAGIC)数据库。这个甲骨文9i数据库源于我们实验室最初通过表达序列标签(EST)的产生和分析进行基因发现的工作,随后又专注于通过EST聚类和微阵列评估基因表达。该数据库的MAGIC基因发现部分侧重于从DNA序列中获取的信息及其生物学相关性。除了旨在支持实验室活动的MAGIC SEQ-LIMS外,它还包含几个其他子模式。后者包括用于数据库管理的MAGIC Admin、用于序列处理以及序列和克隆属性的MAGIC Sequence、用于EST聚类结果的MAGIC Cluster、用于支持微卫星和单核苷酸多态性发现的MAGIC Polymorphism以及用于通过BLAST和BLAT进行电子注释的MAGIC Annotation。MAGIC微阵列部分是一个目前符合MIAME标准的数据库,有两个组件。它们是MAGIC Array-LIMS,它使所有信息能够远程输入数据库,以及MAGIC Array Analysis,它提供数据挖掘和可视化功能。由于与MAGIC数据库的所有交互都是通过网络浏览器进行的,因此它不仅非常适合单个研究实验室,也适合为任何距离的客户服务的核心设施。

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