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EGID: an ensemble algorithm for improved genomic island detection in genomic sequences

dc.contributor.authorChe, Dongsheng
dc.contributor.authorHasan, Mohammad Shabbir
dc.contributor.authorWang, Han
dc.contributor.authorFazekas, John
dc.contributor.authorHuang, Jinling
dc.contributor.authorLiu, Qi
dc.date.accessioned2016-06-03T15:21:47Z
dc.date.available2016-06-03T15:21:47Z
dc.date.issued2011
dc.description.abstractGenomic islands (GIs) are genomic regions that are originally transferred from other organisms. The detection of genomic islands in genomes can lead to many applications in industrial, medical and environmental contexts. Existing computational tools for GI detection suffer either low recall or low precision, thus leaving the room for improvement. In this paper, we report the development of our Ensemble algorithm for Genomic Island Detection (EGID). EGID utilizes the prediction results of existing computational tools, filters and generates consensus prediction results. Performance comparisons between our ensemble algorithm and existing programs have shown that our ensemble algorithm is better than any other program. EGID was implemented in Java, and was compiled and executed on Linux operating systems. EGID is freely available at http://www5.esu.edu/cpsc/bioinfo/software/EGID.en_US
dc.identifier.citationBioinformation; 7:6 p. 311-314en_US
dc.identifier.issn0973-2063
dc.identifier.pmidpmc3280502en_US
dc.identifier.urihttp://hdl.handle.net/10342/5442
dc.relation.urihttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC3280502/en_US
dc.subjectGenomic islandsen_US
dc.subjectEnsemble algorithmen_US
dc.subjectBacterial genomesen_US
dc.titleEGID: an ensemble algorithm for improved genomic island detection in genomic sequencesen_US
dc.typeArticleen_US
ecu.journal.issue6en_US
ecu.journal.nameBioinformationen_US
ecu.journal.pages311-314en_US
ecu.journal.volume7en_US

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