Re-engineering the MEGA software package

重新设计 MEGA 软件包

• 批准号: 7473904
• 负责人: Sudhir Kumar
• 金额: $ 25.56万
• 依托单位: ARIZONA STATE UNIVERSITY-TEMPE CAMPUS
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-01 至 2010-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7473904
• 关键词: 64-bit computing; AIDS/HIV problem; Address; Adoption; Affect; Agriculture; Automation; Bioinformatics; Biological; Categories; Class; Code; Communities; Comparative Genomic Analysis; Compatible; Complex; Computational Biology; Computational Science; Computer Workstations; Computer software; Data; Data Analyses; Data Files; Data Set; Development; Discipline; Engineering; Evolution; Experimental Designs; Extensible Markup Language; Face; Feedback; Future; Genes; Genome; Genomics; Goals; Growth; Imagery; Individual; Informatics; Institution; Instruction; Investigation; Laboratories; Laboratory Scientists; Large-Scale Sequencing; Left; Longevity; Methodology; Methods; Modernization; Molecular; Molecular Evolution; Movement; Multimedia; Nature; Numbers; Ontology; Output; Pattern; Performance; Plug-in; Principal Investigator; Process; Protocols documentation; Publications; Purpose; Range; Reading; Recording of previous events; Research; Research Personnel; Resources; Rest; Running; Sequence Analysis; Software Engineering; Software Tools; Source Code; Specialist; Standards of Weights and Measures; Statistical Methods; Students; System; Techniques; Technology; Time; Training; Update; Video Games; Visual; base; biological research; biomedical scientist; comparative; computerized tools; cost; design; file format; functional genomics; genetic analysis; genome sequencing; graphical user interface; innovation; interest; interoperability; novel; programs; research study; scripting interface; software development; success; tool; usability; user-friendly

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.

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 多篇涉及多个生物研究学科的研究出版物引用，并且已被超过 50,000 名代表来自非营利和商业机构的学生、教育工作者和研究人员的个人下载。为了让 MEGA 能够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，我们计划解决对 MEGA 保持可用和可扩展以应对大规模比较基因组学分析快速变化的能力影响最大的问题和挑战。因此，我们的目标是重构 MEGA 的源代码，以记录软件背后的大量源代码，并对 MEGA 的计算核心进行模块化，作为实现其他重新设计目标的有利步骤。模块化计算核心可以实现插件扩展性机制，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，该接口可以将 MEGA 的功能扩展到迭代、多数据集分析协议，这些协议在大规模序列分析工作中已变得司空见惯。大规模序列分析的复杂性通常需要协调使用众多的生物信息学软件工具。认识到这一需求，我们计划增强 MEGA 与不同数据文件格式互操作的能力，包括集成对流行和标准化输入/输出文件格式的支持。在MEGA漫长的发展历史中，普通消费级计算机工作站的功能已经发生了显着的发展。虽然最初是为计算密集型多媒体应用而开发的，但我们计划将 64 位计算和 SIMD 技术集成到 MEGA 中，以大大增强其大规模分析的性能。这些核心软件增强功能将有助于延长 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。