Detecting genomic islands using bioinformatics approaches

@article{Langille2010DetectingGI,
  title={Detecting genomic islands using bioinformatics approaches},
  author={Morgan G. I. Langille and William W. L. Hsiao and Fiona S. L. Brinkman},
  journal={Nature Reviews Microbiology},
  year={2010},
  volume={8},
  pages={373-382}
}
Bacterial genomes contain clusters of genes that are acquired by horizontal transfer, called genomic islands (GIs). GIs are frequently associated with microbial adaptations that are of medical and environmental interest, and they have had a substantial impact on bacterial evolution. Therefore, there is growing interest in efficiently identifying GIs in newly sequenced bacterial genomes. Several computational methods for detecting GIs have been developed recently, presenting researchers with a… 
Computational methods for predicting genomic islands in microbial genomes
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TLDR
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TLDR
A novel method to predict GIs that is built upon mean shift clustering algorithm that does not require any information regarding the number of clusters, and the bandwidth parameter is automatically calculated based on a heuristic approach.
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TLDR
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TLDR
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High-Density Transcriptional Initiation Signals Underline Genomic Islands in Bacteria
TLDR
A new sliding window method, GIST, Genomic-island Identification by Signals of Transcription, is developed, which demonstrates high sensitivity in detecting GIs harboring genes with biased GI-like function, preferred subcellular localization, skewed GC property, shorter gene length and biased “non-optimal” codon usage.
An Integrative Approach for Genomic Island Prediction in Prokaryotic Genomes
TLDR
It is reported, for the first time, that gene information and inter-genic distance are different between genomic islands and non-genomic islands, and it is concluded that the incorporation of geneInformation and intergenic distance could improve genomic island prediction accuracy.
EuGI: a novel resource for studying genomic islands to facilitate horizontal gene transfer detection in eukaryotes
TLDR
The previously developed GI prediction tool, SeqWord Gene Island Sniffer (SWGIS), is modified to predict GIs in eukaryotic chromosomes and the EuGI database, which houses GIs identified in 66 different eUKaryotic species, and theEuGI web-resource, provide the first comprehensive resource for studying HGT in Eukaryotes.
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