By Topic

EGGS: Extraction of Gene Clusters Using Genome Context Based Sequence Matching Techniques

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)

Functionally related genes co-evolve, probably due to selection pressures during evolution, This phenomenon leads to conservation of gene clusters across genomes, especially in microbial genomes. In this paper, we propose novel iterative constraint relaxation algorithms which make use of genome contexts to effectively remove noise and extract gene clusters: PairEGGS that generates gene clusters in a pair of genomes and MultiEGGS that combines gene clusters from genome pairs. Experiments showed that PairEGGS produced significantly larger gene clusters than existing algorithms, say FISH, and MultiEGGS was able to find gene clusters as large as of 118 genes that are common to three genomes. Both PairEGGS and MultiEGGS run fast enough to provide service on the web.

Published in:

Bioinformatics and Biomedicine, 2007. BIBM 2007. IEEE International Conference on

Date of Conference:

2-4 Nov. 2007