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

dc.contributor.authorGanesan, Hamilton
dc.contributor.authorRakitianskaia, A.S. (Anastassia Sergeevna)
dc.contributor.authorDavenport, Colin F.
dc.contributor.authorTummler, Burkhard
dc.contributor.authorReva, Oleg N.
dc.contributor.emailannar@cs.up.ac.zaen_US
dc.date.accessioned2009-04-16T11:47:49Z
dc.date.available2009-04-16T11:47:49Z
dc.date.issued2008-08
dc.description.abstractBACKGROUND: 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.citationGanesan, 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.issn1471-2105
dc.identifier.other10.1186/1471-2105-9-333
dc.identifier.urihttp://hdl.handle.net/2263/9667
dc.language.isoenen_US
dc.publisherBioMed Centralen_US
dc.rightsBioMed Centralen_US
dc.subjectSeqWord Genome Browseren_US
dc.subjectOnline toolen_US
dc.subjectData miningen_US
dc.subjectSequence analysisen_US
dc.subjectData sequencesen_US
dc.subjectVisualizationen_US
dc.subject.lcshBioinformatics
dc.subject.lcshMicrobial genomics
dc.subject.lcshOligonucleotides -- Research
dc.titleThe SeqWord Genome Browser : an online tool for the identification and visualization of atypical regions of bacterial genomes through oligonucleotide usageen_US
dc.typeArticleen_US

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