SBIR Phase I: A Bioinformatics Software Application for Visualizing and Evaluating Evolutionary Networks of Next-Generation Sequences

这个小企业创新研究（SBIR）项目的更广泛的影响/商业潜力是解决与大规模下一代测序（NGS）相关的大量未分类、嘈杂数据的理解、分析和可视化方面的挑战。这些项目往往侧重于病原体传播模式、耐药性和一般流行病学，并采用一种称为“聚类”的过程；然而，当前的聚类工具都是初级的、不直观的、缺乏文档记录的，并且在数据管理和可视化方面提供的帮助很少。目标是开发用于个性化环境（CASPER）中的聚类和关联序列的软件。该软件将为NGS序列分析带来急需的最先进的软件工程和可视化技术，从而发现目前被忽视的不同数据类型中的相关性。此外，该软件还满足了集成生物信息学的商业需求，利用现代创新技术加快发现，增强最终用户体验。这将提高研究人员应对重大卫生挑战、进行生物学研究和制定有效干预措施以预防和治疗疾病的能力。这个SBIR一期项目提出开发一个生物信息学应用程序，为生物学研究人员设计，以探索非常大的序列数据集中的进化关系。这些数据通常与多个注释相关联，并且在获取它们之间关系的有意义的可视化表示方面存在耗时障碍，特别是在与地理空间、人口统计和/或时间数据结合使用时。此外，虽然许多生物信息学应用/方法专注于实现单一的分析任务，但拟议的软件广泛关注最终用户，因此有效和准确的数据处理与丰富而有意义的图形输出相结合。此外，它将提供一个图形数据库管理系统（GDBS），围绕研究人员的数据进行导入，从而减少错误。链接到分析结果的数据库允许快速的结果过滤以及随着时间的推移数据集扩展的即时更新。集成的可视化工具允许研究人员生成各种网络图形，可以显示结果如何随时间变化。在第一阶段，目标是专注于开发一个框架来优化最终用户体验（例如，速度、直观的设计、有用的结果格式）。该项目汇集了软件设计、计算机建模、数据可视化、生物信息学、遗传分析和流行病学领域的一群强大而独特的科学家。

The broader impact/commercial potential of this Small Business Innovative Research (SBIR) project is to addresses challenges in understanding, analyzing, and visualizing data from large sets of unsorted, noisy data associated with massive next generation sequencing (NGS). These projects frequently are focused on pathogen transmission patterns, drug resistance, and general epidemiology and employ a process called "clustering"; however, current clustering tools are rudimentary, not intuitive, poorly documented and provide little help with data management and visualization. The goal is to develop software for Clustering and Associating Sequences in a Personalized Environment (CASPER). This software will bring much needed state-of-the-art software engineering and visualization technology to NGS sequence analysis that results in finding correlations in disparate data-types that are currently overlooked. Further, this software addresses commercial demands for integrated bioinformatics that speed discovery using contemporary and innovative technologies that enhance the end-user experience. This will increase the ability of researchers to combat major health challenges, perform biological research and develop effective interventions to prevent and treat illness.This SBIR Phase I project proposes to develop a bioinformatics application designed for biological researchers to explore the evolutionary relationships in very large sequence data sets. These data are commonly associated with multiple annotations and there are time-consuming hurdles in acquiring a meaningful visual representation of their relationships, especially in combination with geospatial, demographic and/or temporal data. Further, while many bioinformatics applications/approaches focus on achieving a single analytical task, the proposed software focuses extensively on the end-user, so that efficient and accurate data processing are combined with rich and meaningful graphical outputs. In addition, it will provide a graphical database management system (GDBS) built around the researcher's data as it is imported, resulting in fewer errors. A database linked to analytical results allows for rapid result filtering as well as instantaneous updates as data sets expand over time. Integrated visualization tools allow researchers to produce varied network graphics that can show how results change over time. In Phase I, the goal is to focus on developing a framework to optimize the end-user experience (e.g., speed, intuitive design, useful formatting of results). The project brings together a powerful and unique group of scientists in the fields of software design, computer modeling, data visualization, bioinformatics, genetic analysis and epidemiology.