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By David Langenberger, Sebastian Bartschat, Jana Hertel, Steve Hoffmann, Hakim Tafer (auth.), Osmar Norberto de Souza, Guilherme P. Telles, Mathew Palakal (eds.)

This publication constitutes the court cases of the sixth Brazilian Symposium on Bioinformatics, BSB 2011, held in Brasília, Brazil, in August 2011.
The eight complete papers and four prolonged abstracts awarded have been conscientiously peer-reviewed and chosen for inclusion during this booklet. The BSB themes of curiosity disguise many parts of bioinformatics that variety from theoretical points of difficulties in bioinformatics to functions in molecular biology, biochemistry, genetics, and linked subjects.

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Additional info for Advances in Bioinformatics and Computational Biology: 6th Brazilian Symposium on Bioinformatics, BSB 2011, Brasilia, Brazil, August 10-12, 2011. Proceedings

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S. Adi 0 1100 2200 3300 4400 5500 6600 7700 8800 9900 11000 7700 8800 9900 11000 TOMM6 Real TOMM6 H1,H2,H3 ZNF418 Real ZNF418 H3 IRF1 Real IRF1 H2 0 1100 2200 3300 4400 5500 6600 Fig. 1. Example os mispredictions presented by the heuristics Despite the aforementioned drawbacks, the values in Table 1 shows that, with exception of the second heuristic, the first and third ones outperform all the other gene prediction tools at the exon level, including Procrustes, that implements the spliced alignment algorithm.

Despite the number of gene predictions tool available, the task of gene finding remains an open problem and an interesting subject of research. In this work, we studied a generalization of a well known formulation of the exon assembly problem, called multiple spliced alignment problem, and used the related results in the development of three comparative-based heuristics to the gene prediction task. In order to assess how adequate is the proposed formulation and the related heuristics, they were implemented and the resulting programs were tested and Gene Prediction by Multiple Spliced Alignment 33 compared with other six comparative-based gene prediction tools by means of a benchmark including 240 human genomic sequences.

Hum. Retroviruses 24(12), 1497–1502 (2008) 18. : Selecting anti-HIV therapies based on a variety of genomic and clinical factors. Bioinformatics 24, i399–i406 (2008) 19. : Host sequence motifs shared by HIV predict response to antiretroviral therapy. BMC Med. br Abstract. With recent advances in sequencing technologies, a huge amount of DNA sequences become available year after year. In order to obtain useful information on these sequences, we need to process them in search of biologically meaningful regions.

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