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Int. J. Mol. Sci. 2012, 13(3), 3134-3144;

Prediction of Genomic Islands in Three Bacterial Pathogens of Pneumonia

Center of Bioinformatics and Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
Author to whom correspondence should be addressed.
Received: 31 January 2012 / Revised: 20 February 2012 / Accepted: 1 March 2012 / Published: 7 March 2012
(This article belongs to the Section Biochemistry)
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Pneumonia is one kind of common infectious disease, which is usually caused by bacteria, viruses, or fungi. In this paper, we predicted genomic islands in three bacterial pathogens of pneumonia. They are Chlamydophila pneumoniae, Mycoplasma pneumoniae and Streptococcus pneumoniae, respectively. For each pathogen, one clinical strain is involved. After implementing the cumulative GC profile combined with h and BCN index, eight genomic islands are found in three pathogens. Among them, six genomic islands are found to have mobility elements, which constitute a kind of conserved character of genomic islands, and this introduces the possibility that they are genuine genomic islands. The present results show that the cumulative GC profile when combined with h and BCN indexes is a good method for predicting genomic islands in bacteria and it has lower false positive rate than the SIGI method. Specially, three genomic islands are found to contain clusters of genes coding for production of virulence factors and this is useful for research into the pathogenicity of these pathogens and helpful for the treatment of diseases caused by them. View Full-Text
Keywords: genomic islands; pneumonic pathogens; cumulative GC profile genomic islands; pneumonic pathogens; cumulative GC profile
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Guo, F.-B.; Wei, W. Prediction of Genomic Islands in Three Bacterial Pathogens of Pneumonia. Int. J. Mol. Sci. 2012, 13, 3134-3144.

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