The SeqWord Genome Browser : an online tool for the identification and visualization of atypical regions of bacterial genomes through oligonucleotide usage

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dc.contributor.author Ganesan, Hamilton
dc.contributor.author Rakitianskaia, A.S. (Anastassia Sergeevna)
dc.contributor.author Davenport, Colin F.
dc.contributor.author Tummler, Burkhard
dc.contributor.author Reva, Oleg N.
dc.date.accessioned 2009-04-16T11:47:49Z
dc.date.available 2009-04-16T11:47:49Z
dc.date.issued 2008-08
dc.description.abstract BACKGROUND: Data mining in large DNA sequences is a major challenge in microbial genomics and bioinformatics. Oligonucleotide usage (OU) patterns provide a wealth of information for large scale sequence analysis and visualization. The purpose of this research was to make OU statistical analysis available as a novel web-based tool for functional genomics and annotation. The tool is also available as a downloadable package. RESULTS: The SeqWord Genome Browser (SWGB) was developed to visualize the natural compositional variation of DNA sequences. The applet is also used for identification of divergent genomic regions both in annotated sequences of bacterial chromosomes, plasmids, phages and viruses, and in raw DNA sequences prior to annotation by comparing local and global OU patterns. The applet allows fast and reliable identification of clusters of horizontally transferred genomic islands, large multi-domain genes and genes for ribosomal RNA. Within the majority of genomic fragments (also termed genomic core sequence), regions enriched with housekeeping genes, ribosomal proteins and the regions rich in pseudogenes or genetic vestiges may be contrasted. CONCLUSION: The SWGB applet presents a range of comprehensive OU statistical parameters calculated for a range of bacterial species, plasmids and phages. en_US
dc.identifier.citation Ganesan, H, Rakitianskaia, AS, Davenport, CF, Tümmler, B & Reva, ON 2008, 'The SeqWord Genome Browser : an online tool for the identification and visualization of atypical regions of bacterial genomes through oligonucleotide usage', BMC Bioinformatics, vol. 9, no. 7, pp. 1-13. [http://www.biomedcentral.com/bmcbioinformatics/] en_US
dc.identifier.issn 1471-2105
dc.identifier.other 10.1186/1471-2105-9-333
dc.identifier.uri http://hdl.handle.net/2263/9667
dc.language.iso en en_US
dc.publisher BioMed Central en_US
dc.rights BioMed Central en_US
dc.subject SeqWord Genome Browser en_US
dc.subject Online tool en_US
dc.subject Data mining en_US
dc.subject Sequence analysis en_US
dc.subject Data sequences en_US
dc.subject Visualization en_US
dc.subject.lcsh Bioinformatics
dc.subject.lcsh Microbial genomics
dc.subject.lcsh Oligonucleotides -- Research
dc.title The SeqWord Genome Browser : an online tool for the identification and visualization of atypical regions of bacterial genomes through oligonucleotide usage en_US
dc.type Article en_US


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