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

SBIR 第一阶段：用于可视化和评估下一代序列进化网络的生物信息学软件应用程序

• 批准号: 1648053
• 负责人: Susanna Lamers
• 金额: $ 22.5万
• 依托单位: Bioinfoexperts, LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-12-01 至 2017-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1648053&HistoricalAwards=false
• 关键词: SBIR; Phase; Bioinformatics; Software; Application

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.

这个小企业创新研究（SBIR）项目的更广泛的影响/商业潜力是解决理解，分析和可视化与大规模下一代测序（NGS）相关的大量未分类，噪声数据的挑战。这些项目通常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，目前的聚类工具是基本的，不直观，记录不佳，对数据管理和可视化几乎没有帮助。目标是开发个性化环境中的聚类和关联序列（CASPER）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，从而找到目前被忽视的不同数据类型的相关性。此外，该软件还满足了对集成生物信息学的商业需求，这些集成生物信息学使用当代创新技术来加速发现，从而增强最终用户体验。 这将提高研究人员应对重大健康挑战的能力，进行生物研究，并开发有效的干预措施，以预防和治疗疾病。SBIR第一阶段项目提出开发一个生物信息学应用程序，旨在为生物研究人员探索非常大的序列数据集的进化关系。这些数据通常与多个注释相关联，并且在获取其关系的有意义的视觉表示方面存在耗时的障碍，特别是与地理空间，人口统计和/或时间数据相结合。此外，虽然许多生物信息学应用程序/方法侧重于实现单一的分析任务，但所提出的软件广泛关注最终用户，因此高效准确的数据处理与丰富而有意义的图形输出相结合。此外，它还将提供一个图形数据库管理系统（GDBS），该系统围绕研究人员导入的数据构建，从而减少错误。与分析结果链接的数据库允许快速结果过滤以及随着数据集随着时间的推移而扩展的即时更新。集成的可视化工具使研究人员能够生成各种网络图形，这些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优化最终用户体验的框架（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批强大而独特的科学家。