EGID: an ensemble algorithm for improved genomic island detection in genomic sequences |
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Authors: | Che Dongsheng Hasan Mohammad Shabbir Wang Han Fazekas John Huang Jinling Liu Qi |
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Institution: | 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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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. |
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Keywords: | Bacterial genomes Ensemble algorithm Genomic islands |
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