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Title |
EGID: an ensemble algorithm for improved genomic island detection in genomic sequences |
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Authors |
Dongsheng Che1*, Mohammad Shabbir Hasan1, Han Wang1, John Fazekas1, Jinling Huang2, Qi Liu3 |
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Affiliation |
1Department of Computer Science, East Stroudsburg University, East Stroudsburg, PA 18301; 2Department of Biology, East Carolina University, Greenville, NC 27858; 3College of Life Science and Biotechnology, Tongji University, Shanghai, 200092, China.
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dche@po-box.esu.edu; *Corresponding author
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Article Type |
Prediction Model
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Date |
Received November 16, 2011; Accepted November 17, 2011; Published November 20, 2011
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Abstract |
Genomicislands (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.
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Keywords |
Bacterial genomes; Ensemble algorithm; Genomic islands.
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Citation |
Che et al.
Bioinformation 7(6): 311-314 (2011) |
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Edited by |
P Kangueane
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ISSN |
0973-2063
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Publisher |
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License |
This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License. |