生物克隆数据库：一个用于管理DNA序列和基因表达数据的数据库应用程序。

Reuveni Eli, Leshkowitz Dena, Yarden Oded

Department of Plant Pathology and Microbiology, Faculty of Agricultural, Food and Environmental Quality Sciences, The Hebrew University of Jerusalem, Rehovot, Israel.

Appl Bioinformatics. 2005;4(4):277-80. doi: 10.2165/00822942-200504040-00007.

UNLABELLED

BioCloneDB is a user-friendly database with a web interface to assist molecular genetics laboratories in managing a local repository of sequence information linked to DNA clones. This tool is designed to assist in high-throughput sequence and gene expression projects, providing a link between both types of information. The unique feature of the application is the automation of batch sequence annotation following BLAST((R)) searches, which is supported by easy-to-use web interfaces. Furthermore, any set of sequences can be annotated against any sequence database. This replaces the need to perform and analyse individual web BLAST((R)) searches or the need to learn how to produce batch searches and perform analysis in a UNIX((R)) operating system. BioCloneDB is open-source software that can be installed on Linux or UNIX((R)) operating systems. To test the application, we used 1400 expressed sequence tags obtained from the filamentous fungus Neurospora crassa. The results were analysed and compared with published results and they show a significant change due to the accumulation of the data in the nr database (ftp://ftp.ncbi.nih.gov/blast/db/).

AVAILABILITY

BioCloneDB is available for academic use along with documentation, screenshots, database scheme and readme files at http://bioclonedb.agri.huji.ac.il/

CONTACT

Oded Yarden (Oded.Yarden@huji.ac.il).

未标注

BioCloneDB是一个用户友好型数据库，带有网络界面，可协助分子遗传学实验室管理与DNA克隆相关的本地序列信息库。该工具旨在协助高通量测序和基因表达项目，在这两类信息之间建立联系。该应用程序的独特之处在于，在BLAST((R))搜索后可自动进行批量序列注释，这由易于使用的网络界面提供支持。此外，任何一组序列都可以针对任何序列数据库进行注释。这取代了执行和分析单个网络BLAST((R))搜索的需求，也无需学习如何在UNIX((R))操作系统中进行批量搜索和分析。BioCloneDB是开源软件，可安装在Linux或UNIX((R))操作系统上。为测试该应用程序，我们使用了从丝状真菌粗糙脉孢菌获得的1400个表达序列标签。对结果进行了分析，并与已发表的结果进行了比较，结果显示由于nr数据库（ftp://ftp.ncbi.nih.gov/blast/db/）中数据的积累，出现了显著变化。