QAlign: quality-based multiple alignments with dynamic phylogenetic analysis.

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QAlign: quality-based multiple alignments with dynamic phylogenetic analysis.

Bioinformatics. 2003 Aug 12;19(12):1592-3

Authors: Sammeth M, Rothgänger J, Esser W, Albert J, Stoye J, Harmsen D

Abstract
Integrating different alignment strategies, a layout editor and tools deriving phylogenetic trees in a 'multiple alignment environment' helps to investigate and enhance results of multiple sequence alignment by hand. QAlign combines algorithms for fast progressive and accurate simultaneous multiple alignment with a versatile editor and a dynamic phylogenetic analysis in a convenient graphical user interface.

PMID: 12912847 [PubMed - indexed for MEDLINE]

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Divide-and-conquer multiple alignment with segment-based constraints.

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Divide-and-conquer multiple alignment with segment-based constraints.

Bioinformatics. 2003 Oct;19 Suppl 2:ii189-95

Authors: Sammeth M, Morgenstern B, Stoye J

Abstract
A large number of methods for multiple sequence alignment are currently available. Recent benchmarking tests demonstrated that strengths and drawbacks of these methods differ substantially. Global strategies can be outperformed by approaches based on local similarities and vice versa, depending on the characteristics of the input sequences. In recent years, mixed approaches that include both global and local features have shown promising results. Herein, we introduce a new algorithm for multiple sequence alignment that integrates the global divide-and-conquer approach with the local segment-based approach, thereby combining the strengths of those two strategies.

PMID: 14534189 [PubMed - indexed for MEDLINE]

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RIDOM: comprehensive and public sequence database for identification of Mycobacterium species.

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RIDOM: comprehensive and public sequence database for identification of Mycobacterium species.

BMC Infect Dis. 2003 Nov 11;3:26

Authors: Harmsen D, Dostal S, Roth A, Niemann S, Rothgänger J, Sammeth M, Albert J, Frosch M, Richter E

Abstract
BACKGROUND: Molecular identification of Mycobacterium species has two primary advantages when compared to phenotypic identification: rapid turn-around time and improved accuracy. The information content of the 5' end of the 16S ribosomal RNA gene (16S rDNA) is sufficient for identification of most bacterial species. However, reliable sequence-based identification is hampered by many faulty and some missing sequence entries in publicly accessible databases.
METHODS: In order to establish an improved 16S rDNA sequence database for the identification of clinical and environmental isolates, we sequenced both strands of the 5' end of 16S rDNA (Escherichia coli positions 54 to 510) from 199 mycobacterial culture collection isolates. All validly described species (n = 89; up to March 21, 2000) and nearly all published sequevar variants were included. If the 16S rDNA sequences were not discriminatory, the internal transcribed spacer (ITS) region sequences (n = 84) were also determined.
RESULTS: Using 5'-16S rDNA sequencing a total of 64 different mycobacterial species (71.9%) could be identified. With the additional input of the ITS sequence, a further 16 species or subspecies could be differentiated. Only Mycobacterium tuberculosis complex species, M. marinum/M. ulcerans and the M. avium subspecies could not be differentiated using 5'-16S rDNA or ITS sequencing. A total of 77 culture collection strain sequences, exhibiting an overlap of at least 80% and identical by strain number to the isolates used in this study, were found in the GenBank. Comparing these with our sequences revealed that an average of 4.31 nucleotide differences (SD +/- 0.57) were present.
CONCLUSIONS: The data from this analysis show that it is possible to differentiate most mycobacterial species by sequence analysis of partial 16S rDNA. The high-quality sequences reported here, together with ancillary information (e.g., taxonomic, medical), are available in a public database, which is currently being expanded in the RIDOM project http://www.ridom-rdna.de), for similarity searches.

PMID: 14611664 [PubMed - indexed for MEDLINE]

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