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ABI Innovation: Querying massive dynamic biological network databases.

Abstract:.

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. (NSF award page)

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Tamer Kahveci
Last modified: Wed Jul 8 13:48:05 EDT 2015