This article is part of the supplement: Proceedings of the 6th International Conference of the Brazilian Association for Bioinformatics and Computational Biology (X-meeting 2010)

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A singular value decomposition approach for improved taxonomic classification of biological sequences

Anderson R Santos1, Marcos A Santos2, Jan Baumbach3, John A McCulloch1, Guilherme C Oliveira4, Artur Silva5, Anderson Miyoshi1 and Vasco Azevedo1*

Author Affiliations

1 Department of General Biology, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Av. Antônio Carlos, 6627, MG, 31.270-901, Brazil

2 Computer Science Departament, Instituto de Ciências Exatas, Universidade Federal de Minas Gerais, Belo Horizonte, Av. Antonio Carlos, 6627, 31.270-901, MG, Brazil

3 Max Planck Institute for Informatics, Campus E2 1, Saarbrücken, Germany

4 CEBio and Laboratory of Cellular and Molecular Parasitology, Instituto René Rachou, Oswaldo Cruz Foundation, Belo Horizonte, Av. Augusto de Lima 1715, 30190-002, MG, Brazil

5 Genome and Proteome Network of the State of Pará, Universidade Federal do Pará, Belém, R. Augusto Corrêa, 66.075-110, PA, Brazil

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BMC Genomics 2011, 12(Suppl 4):S11  doi:10.1186/1471-2164-12-S4-S11

Published: 22 December 2011

Additional files

Additional file 1:

Qualitative cluster measures. In this document, we elaborate on aspects of the qualitative cluster measures that are not discussed in this paper, such as the demand for specific metrics for clusters based on Linnaean taxonomic classification, how sequences size influence kdcSearch, a proof that amino acid trigams do not occur by chance, how to make a graphic cluster approximation by cladograms, how the evaluated algorithms were executed and the kdcSearch algorithm pseudo-code.

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Additional file 2:

Scilab algorithms and raw data. In this file, we elaborate on aspects of the algorithms and data used in this research. Algorithms were written in Scilab version "5.2.0.1266391513", scilab-5.2.1.

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