SBIR Phase I: Machine Learning Software for Viral Sequence Analysis and Diagnostics

SBIR 第一阶段：用于病毒序列分析和诊断的机器学习软件

• 批准号: 0610688
• 负责人: Gary Fogel
• 金额: $ 10万
• 依托单位: NATURAL SELECTION, INCORPORATED
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-07-01 至 2006-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0610688&HistoricalAwards=false
• 关键词: SBIR; Phase; Machine; Learning; Software

This Small Business Innovative Research (SBIR) Phase I project focuses on developing computational intelligence tools for viral sequence analysis. In contrast to current modeling approaches, the proposed software tool will result in an easily interpreted best model that can be used to better understand the relationship between sequence variations and phenotypic behavior and or response.The research will result in a user friendly software tool that will allow for better predictability of the effect of viral mutations on infectivity, efficacy of the virus as well as aid in the development of antivirals and effect of treatments. This has broad application in viral research and pharmaceutical design.

这个小型企业创新研究（SBIR）第一阶段项目的重点是开发用于病毒序列分析的计算智能工具。与目前的建模方法相比，拟议的软件工具将产生一个易于解释的最佳模型，可用于更好地理解序列变异与表型行为和/或反应之间的关系。该研究将产生一个用户友好的软件工具，可以更好地预测病毒突变对感染性的影响，病毒的功效以及有助于抗病毒药物的开发和治疗效果。 这在病毒研究和药物设计中具有广泛的应用。