SIB: Database and Tool for the Integration and Browsing of Large Scale Image Hhigh-Throughput Screening Data

K. Kozak, M. Kozak, E. Krausz
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Abstract

Data management has become one of the central issues in high-throughput biological screening. In particular high-throughput screening (HTS), applying automated microscopy, requires a system which is capable of storing and analyzing vast amounts of image and numeric data. These data include comprehensive information about the bioactive molecules, the targeted genes, and images as well as their extracted data matrices after acquisition. Here we present a Web-based bioinformatics solution for the management of images from different screening microscopes: the screening image browser (SIB). The following points describe this tool as well as an image retrieval mechanism, both working as a framework for browsing and analyzing screening information. A major outcome of this database is a unique, fully operational, distributed digital library of screening image data accessible to researchers. SIB is a scientific database that enables effective data management accessible through a standard Web-browser interface. The application utilizes a robust security architecture and is designed for efficient data exploration
SIB:集成和浏览大规模图像和高通量筛选数据的数据库和工具
数据管理已成为高通量生物筛选的核心问题之一。特别是高通量筛选(HTS),应用自动化显微镜,需要一个能够存储和分析大量图像和数字数据的系统。这些数据包括生物活性分子、靶基因和图像的综合信息以及采集后提取的数据矩阵。在这里,我们提出了一个基于网络的生物信息学解决方案,用于管理来自不同筛选显微镜的图像:筛选图像浏览器(SIB)。以下几点描述了该工具以及图像检索机制,它们都作为浏览和分析筛选信息的框架。该数据库的一个主要成果是一个独特的、完全可操作的、分布式的筛选图像数据数字图书馆,可供研究人员访问。SIB是一个科学数据库,它支持通过标准web浏览器界面访问有效的数据管理。该应用程序利用健壮的安全体系结构,专为高效的数据探索而设计
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