A gene pattern mining algorithm using interchangeable gene sets for prokaryotes

Background: Mining gene patterns that are common to multiple genomes is an important biological problem, which can lead us to novel biological insights. When family classification of genes is available, this problem is similar to the pattern mining problem in the data mining community. However, when family classification information is not available, mining gene patterns is a challenging problem. There are several well developed algorithms for predicting gene patterns in a pair of genomes, such as FISH and DAGchainer. These algorithms use the optimization problem formulation which is solved using the dynamic programming technique. Unfortunately, extending these algorithms to multiple genome cases is not trivial due to the rapid increase in time and space complexity. Results: In this paper, we propose a novel algorithm for mining gene patterns in more than two prokaryote genomes using interchangeable sets. The basic idea is to extend the pattern mining technique from the data mining co...

• Type: Journal
• Year: 2008
• Where: BMCBI
• Authors: Meng Hu, Kwangmin Choi, Wei Su, Sun Kim, Jiong Yang
• Keywords: BMCBI 2008, Gene Patterns, Genomes, Mining