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

ECU Author/Contributor (non-ECU co-authors, if there are any, appear on document)

Dongsheng Che (Creator)

John Fazekas (Creator)

Mohammad Shabbir Hasan (Creator)

Jinling Huang (Creator)

Qi Liu (Creator)

Han Wang (Creator)

Institution

East Carolina University (ECU )

Web Site: http://www.ecu.edu/lib/

Abstract: Genomic 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.

Additional Information

Publication

Other

Bioinformation; 7:6 p. 311-314

Language: English

Date: 2011

Keywords

Ensemble algorithm, Genomic islands, Bacterial genomes

Email this document to