Development of a comprehensive system for distant homology analysis

2000年，我们的折叠和功能分配系统（FFAS）服务器开创了蛋白质 profile-profile算法，将其应用于蛋白质结构预测。从那时起， 支撑这些算法的基本思想已经在20多个遥远的地方被使用， 同源识别算法，公共FFAS服务器几乎被 1，000名注册用户每天运行数百个作业， 不仅在蛋白质结构预测，而且在功能预测，靶点选择， 结构基因组学和不同蛋白质家族的一般分析。与永 新的蛋白质序列不断增加，其中许多代表新的， 在未表征的家族中，远缘同源性识别的重要性是 不断增长。我们建议加强FFAS的结构和接口， 与这些新类型的应用程序相匹配，将服务器开发为主要资源 用于研究广泛多样的蛋白质家族。我们计划扩大 通过使用调制解调器编程重构FFAS的代码， 实践开发一个模块化的，多阶段的程序准备与其他集成 服务器，以及使用其他程序，开发内部和外部我们的 组，以提高预测过程中每一步的数据质量， 将中间结果导出给用户进行分析。通过扩展分析集， 和可视化工具集成到FFAS服务器中， 界面，我们想让它更容易被一般训练有素的生物学家使用。 最后，我们计划进行重大的硬件更新，以避免延迟提供 用户提交序列的注释。

In 2000, our Fold and Function Assignment System (FFAS) server pioneered protein profile-profile algorithms, applying them to protein structure prediction. Since then, the basic ideas underpinning these algorithms have been used in over 20 distant homology recognition algorithms, and the public FFAS server is used by almost 1,000 registered users running hundreds of jobs per day, applying the results not only in protein structure prediction, but also in function prediction, target selection in structural genomics, and general analysis of diverse protein families. With ever increasing flow of new protein sequence, many of them representing new, uncharacterized families, the importance of distant homology recognition is constantly growing. We propose enhancing the FFAS structure and interface to match these new types of applications, developing the server into a major resource for studying broad and diversified protein families. We plan to extend the usefulness and maintainability of FFAS by restructuring its code using modem programming practices to develop a modular, multistage program ready to be integrated with other servers, as well as use other programs, developed both inside and outside our group, to improve quality of data at each step of the prediction process and also to export intermediate results to the user for analysis. By extending the set of analysis and visualization tools integrated into the FFAS server and improving its user interface, we want to make it easier to be used by a generally trained biologist. Finally, we plan to perform a significant hardware update to avoid delays in providing annotations for user-submitted sequences.