Continued Development and Maintenance of NMRView

描述(由申请人提供)：蛋白质和核酸的结构、动力学和配体结合特性是理解人类疾病机制的关键。此外，能够干预疾病治疗过程的分子的最佳设计依赖于这些相同的性质。核磁共振波谱是获取这一信息的最通用的技术之一。然而，核磁共振的多功能性导致了大量的数据集，每个数据集都可能有助于解决复杂的计算问题。提取由现代核磁共振技术产生的信息在很大程度上是通过计算机软件来促进的，该计算机软件可以以相关的方式操纵、分析和可视地呈现数据集。在过去的10年里，大分子核磁共振科学家使用的主要软件工具之一是NMRView。NMRView的开发商现在是一名独立的研究科学家，这笔赠款将提供资金来维护和进一步开发NMRView。在授予期间的主要目标之一将是重构代码，使其更易维护、更易于理解和更稳定，并将代码作为开源发布。随着每段代码的重构，将开发一个全面的测试和基准测试框架来测试这段代码。同样，每个模块的核心API和脚本接口将被记录在案，使最终用户能够更容易地开发他们自己的NMRView扩展。将开发基于真实世界数据集的教程，以帮助学习NMRView和现代核磁共振技术。现有的模块将进行优化，并开发新的模块，以解决核磁共振中最先进的技术。这方面的一个例子将是自动分配例程的优化，以促进它们在常规核磁共振研究和高通量结构生物学倡议中的使用。在这一过程中，将使用最先进的计算技术来提供更先进的可视化界面，并提高NMRView的可扩展性。

DESCRIPTION (provided by applicant): The structure, dynamics and ligand binding specificity of proteins and nucleic acids are properties that are key to an understanding of the mechanisms of human disease. Furthermore, the optimal design of molecules that can intervene therapeutically in disease processes relies on these same properties. NMR spectroscopy is one of the most versatile techniques to get this information. The very versatility of NMR, however, leads to a multitude of data sets, each of which potentially contributes to the solution of a complex computational problem. Extracting the information generated by modern NMR techniques is largely facilitated with computer software that can manipulate, analyze and visually present the data sets in a correlated manner. For the past 10 years, one of the primary software tools used by macromolecular-NMR scientists has been NMRView. The developer of NMRView is now an independent research scientist and this grant will provide the funding to maintain and further develop NMRView. One of the primary goals during this granting period will be to refactor the code to make it more maintainable, understandable and stable and to release the code as open source. As each section of code is refactored, a comprehensive testing and benchmarking framework will be developed to test that section of code. Similarly the core API and scripting interface for each module will be documented allowing end-users to more easily develop their own extensions of NMRView. Tutorials, based on real-world data sets, will be developed to aid in the learning of both NMRView and modern NMR techniques. Existing modules will be optimized and new modules developed for addressing state-of-the-art techniques in NMR. An example of this will be the optimization of automated assignment routines to facilitate their use in both conventional NMR research and high throughput structural biology initiatives. During this process, state-of-the-art computational techniques will be used to provide both a more advanced visualization interface and to improve the scalability of NMRView.