Re-engineering the MEGA software package

描述（由申请人提供）：本提案的目的是重新设计分子进化遗传学分析软件（MEGA）的源代码。在过去的13年里，MEGA已被6,000多份研究出版物引用，涵盖了各种生物研究学科，并已被来自非营利和商业机构的学生，教育工作者和研究人员的50，000多名独特的个人下载。为了让MEGA继续满足处于实验设计、信息学和发现前沿的基因组学研究人员的需求，我们必须解决影响其未来前景的几个主要技术问题。特别是，我们计划解决的问题和挑战，有最显着的影响MEGA的能力，保持可用性，并成为可扩展的，以应对快速变化的大规模比较基因组学分析的脸。因此，我们的目标是重构MEGA的源代码，努力记录软件背后的大量源代码，并将MEGA的计算核心模块化，作为实现其他再工程目标的一个有利步骤。模块化计算核心实现了插件扩展机制，使用户社区能够发展和增强MEGA，以满足其日益多样化和快速变化的需求。它还支持应用程序脚本接口的实现，这可以将MEGA的功能扩展到迭代的多数据集分析协议，这些协议在大规模序列分析工作中变得越来越普遍。大规模序列分析的复杂性往往需要协调使用多种生物信息学软件工具。认识到这一需求，我们计划增强MEGA与各种数据文件格式进行互操作的能力，包括对流行的和标准化的输入/输出文件格式的集成支持。在MEGA漫长的发展历史中，普通消费级计算机工作站的功能有了显著的发展。虽然最初开发的计算密集型多媒体应用程序，我们计划将64位计算和SIMD技术集成到MEGA，以大大提高其性能的大规模分析。这些核心软件的增强将有助于MEGA在分子进化、生物信息学、功能基因组学、计算生物学和基础生物医学应用中的使用寿命。

DESCRIPTION (provided by applicant): The purpose of this proposal is to re-engineer the source code of the Molecular Evolutionary Genetics Analysis software (MEGA). Over the past 13 years, MEGA has been cited in more than 6,000 research publications spanning a diverse range of biological research disciplines, and it has been downloaded by more than 50,000 unique individuals representing students, educators and investigators from non-profit and commercial institutions. In order for MEGA to continue to address the needs of genomics researchers at the forefront of experimental design, informatics, and discovery, we must address several major technical issues affecting its future prospects. In particular, we plan to address the issues and challenges that have the most significant impact on MEGA's ability to remain useable and to become extensible to respond to the rapidly changing face of large-scale comparative genomics analysis. Therefore, we aim to refactor MEGA's source code in an effort to document the vast body of source code behind the software, and to modularize MEGA's computational core as an enabling step toward the implementation of additional re-engineering goals. A modular computational core enables the implementation of a plug-in extensibility mechanism that empowers the user community to evolve and enhance MEGA for their increasingly diverse and rapidly changing needs. It also enables the implementaion of an application scripting interface, which can extend MEGA's capabilities to the iterative, multi-dataset analysis protocols that are becoming commonplace in large-scale sequence analysis endeavors. The complexity of large-scale sequence analyses often requires the coordinated use of nemerous bioinformatics software tools. Recognizing this need, we plan to augment MEGA's ability to interoperate with diverse data file formats, including integratation of support for popular as well as standardized input/output file formats. During MEGA's long development history, the capabilities of the average, consumer-grade computer workstation have evolved significantly. Although initially developed for computationally intensive multimedia applications, we plan to integrate 64-bit computing and SIMD technology into MEGA to greatly enhance its performance for large-scale analysis. These core software enhancements will contribute to the longevity of MEGA for use in molecular evolution, bioinformatics, functional genomics, computational biology, and basic biomedicine applications.