ITR: An Active, Personalized, Adaptive, Multi-format Biological Information Delivery System

ITR：主动、个性化、自适应、多格式生物信息传递系统

• 批准号: 0081944
• 负责人: Snehasis Mukhopadhyay
• 金额: $ 49.43万
• 依托单位: Indiana University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-09-01 至 2004-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0081944&HistoricalAwards=false
• 关键词: ITR; Active; Personalized; Adaptive; Multi

The explosive growth of biological information sources, available over the Internet, has given rise to both opportunities and challenges for biological and medical researchers. The opportunities they provide are both scientific (e.g., understanding the information encoded in elementary biological structures) as well as technological (e.g., new drug discovery). The challenges, on the other hand, lie in how to efficiently discover, among the vast volume of information, the items that are relevant or interesting to a given researcher. The objective of the proposed research is to investigate related basic research problems and develop a biological information delivery system in a collaborative project between computer scientists, information scientists, and biological researchers. The specific plans include developing methods to make the proposed system pro-active (surveying evolving on-line sources for relevant information), personalized (cognizant of a particular researcher's interests), adaptive (able to react to changes in the information sources as well as user interests or objectives), and capable of integrating multi-format data. The impact of this research is a significant enhancement in the ability of students and researchers in biological sciences to efficiently utilize on-line resources, while generating methods for computerized analysis of biological data and providing computerized support for new scientific discovery.

通过因特网获得的生物信息源的爆炸性增长给生物和医学研究人员带来了机遇和挑战。 他们提供的机会都是科学的（例如，理解基本生物结构中编码的信息）以及技术（例如，新药发现）。 另一方面，挑战在于如何在大量信息中有效地发现与特定研究人员相关或感兴趣的项目。本研究的目的是探讨相关的基础研究问题，并在计算机科学家、信息科学家和生物研究人员之间的合作项目中开发生物信息传递系统。 具体计划包括制定方法，使拟议的系统具有主动性（调查有关信息的不断发展的在线来源）、个性化（认识到特定研究人员的兴趣）、适应性（能够对信息来源的变化以及用户的兴趣或目标作出反应）和能够整合多种格式的数据。这项研究的影响是在生物科学的学生和研究人员有效地利用在线资源的能力显着提高，同时生成生物数据的计算机分析方法，并为新的科学发现提供计算机支持。