ABI Innovation: Querying Massive Dynamic Biological Network Databases

ABI创新：查询海量动态生物网络数据库

• 批准号: 1262451
• 负责人: Tamer Kahveci
• 金额: $ 49.26万
• 依托单位: University of Florida
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-07-01 至 2018-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1262451&HistoricalAwards=false
• 关键词: ABI; Innovation; Querying; Massive; Dynamic

Understanding the functions served by different biological entities, such as genes, proteins and metabolites, through interactions in biological networks has been a prime goal in biological studies. One promising way to reach this goal is to perform comparative analysis among biological networks. Recently, there has been significant work in collecting and constructing biological networks. As a result, enormous amount of network data is already available. Biological databases today are very large in size and dynamic in nature. This project aims to develop scalable algorithms and tools that enable comparative analysis of very large and dynamic biological network databases. More specifically, it addresses the following problems. i) Develop scalable and accurate algorithms that allow comparing pairs of biological networks quickly while ensuring mathematically provable confidence bounds on the optimality of the results. ii) Develop efficient mining methods tailored to find small sets of representative subnetworks in massive sets of alternative biological network topologies. iii) Develop dynamic indexing methods for searching subnetworks in large collections of biological databases that can adapt to changes in the database (i.e., insertion of new networks, interactions or molecules as well as removal of existing ones) and the query network structure.This project will have both practical and theoretical impact. The developed methods will enable mapping subnetworks of different networks with similar functions. This will improve our understanding of how organisms operate through interactions. The primary impact of this project will be on applications that involve biological networks. It will also impact the studies on other fields such as social networks, distributed computing and homeland security, where a set of operations depend on each other through a complex network. The PI will organize workshops and seminars to disseminate this project throughout the research community. Finally, the code developed as a part of this project will serve as an excellent educational tool to analyze and query biological networks.

了解不同生物学实体（例如基因，蛋白质和代谢产物）通过生物网络中的相互作用的功能一直是生物学研究中的主要目标。实现这一目标的一种有希望的方法是在生物网络之间进行比较分析。 最近，在收集和构建生物网络方面已经做出了重要工作。 结果，已经可用了大量的网络数据。当今的生物数据库的大小和动态性质非常大。该项目旨在开发可扩展的算法和工具，以实现非常大型和动态的生物网络数据库的比较分析。 更具体地说，它解决了以下问题。 i）开发可扩展和准确的算法，以允许快速比较生物网络对，同时确保数学上可证明的置信度在结果的最佳性方面。 ii）开发量身定制的有效的采矿方法，以在大量替代生物网络拓扑结构集中找到一小部分代表性子网。 iii）开发动态索引方法，用于在大量的生物数据库中搜索子网，这些方法可以适应数据库中的变化（即插入新网络，交互或分子以及删除现有的网络）和查询网络结构。这些项目将具有实用和理论上的影响。 开发的方法将启用具有相似功能的不同网络的映射子网。这将提高我们对生物如何通过相互作用进行操作的理解。该项目的主要影响是对涉及生物网络的应用。 它还将影响对其他领域的研究，例如社交网络，分布式计算和国土安全性，其中一组操作通过复杂的网络相互依赖。 PI将组织研讨会和研讨会，以在整个研究社区中传播该项目。最后，作为该项目的一部分而开发的代码将成为分析和查询生物网络的出色教育工具。