SEQUENCE ANALYSIS SOFTWARE DEVELOPMENT

这个子项目是利用资源的许多研究子项目之一。 由NIH/NCRR资助的中心拨款提供。对子项目的主要支持 子项目的首席调查员可能是由其他来源提供的， 包括美国国立卫生研究院的其他来源。为子项目列出的总成本可能 表示该子项目使用的中心基础设施的估计数量， 不是由NCRR赠款提供给次级项目或次级项目工作人员的直接资金。 序列比对和结构同源性建模的软件工具必须随着各种基因组项目和技术(如DNA微阵列)产生的大量新数据而发展。许多常用的生物信息学程序还没有利用在Python、Java和基于Web的界面等领域取得的技术进步。我们设计并实施了一些计划，以利用这些新技术，使信息学家/科学家拥有更友好和更高效的工作环境。我们的软件工具有助于实现序列数据的数据处理流水线自动化和结果的便捷管理。我们正在为对结构研究感兴趣的分子生物学家设计Perl和Python应用程序，以便使丰富的可用的Unix序列分析和同源建模工具像浏览Web一样易于使用。此外，我们打算为许多更常规的数据分析任务开发自动化分析工具。生物计算、可视化和信息学资源(RBVI)为这项跨学科的工作提供了独特的背景，通过我们与分子生物学家和其他科学家的合作，我们开发的工具正在对更广泛的科学界产生重要影响。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Software tools for sequence alignments and structure homology modeling must evolve with the large volume of new data being produced by the various genome projects and technologies such as DNA microarrays. Many of the commonly used bioinformatics programs have yet to take advantage of the technological advances made in areas such as Python, Java, and web-based interfaces. We have designed and implemented programs to take advantage of these new technologies to enable the informaticist/scientist to have a more user-friendly and efficient working environment. Our software tools help automate the data processing pipeline for sequence data and the facile management of results. We are designing Perl and Python applications for molecular biologists interested in structure studies in order to make the wealth of available UNIX sequence analysis and homology modeling tools as easy to use as browsing the Web. Further, we intend to develop automated analysis tools for many of the more routine data analysis tasks. The Resource for Biocomputing, Visualization, and Informatics (RBVI) offers a unique context for this interdisciplinary work, and though our collaborations with molecular biologists and other scientists the tools we develop are having an important impact on the broader scientific community.