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Roberto T. Alves, Myriam R. Delgado, Alex A. Freitas's Advances in Bioinformatics and Computational Biology: Third PDF

By Roberto T. Alves, Myriam R. Delgado, Alex A. Freitas (auth.), Ana L. C. Bazzan, Mark Craven, Natália F. Martins (eds.)

ISBN-10: 3540855564

ISBN-13: 9783540855569

ISBN-10: 3540855572

ISBN-13: 9783540855576

This publication constitutes the refereed complaints of the 3rd Brazilian Symposium on Bioinformatics, BSB 2008, held in Sao Paulo, Brazil, in August 2008 - co-located with IWGD 2008, the foreign Workshop on Genomic Databases.

The 14 revised complete papers and five prolonged abstracts have been conscientiously reviewed and chosen from forty-one submissions. The papers deal with a vast diversity of present themes in computational biology and bioinformatics that includes unique examine in laptop technological know-how, arithmetic and facts in addition to in molecular biology, biochemistry, genetics, drugs, microbiology and different existence sciences.

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Additional info for Advances in Bioinformatics and Computational Biology: Third Brazilian Symposium on Bioinformatics, BSB 2008, Santo André, Brazil, August 28-30, 2008. Proceedings

Example text

The time needed for the search would be to high even for the smaller proteins. 6 Discussion The results show that, although the discrete models presented previously [5] are well optimized for backbone fitting, when side chains are used and clashes are disallowed the accuracy decreases greatly for some proteins. For small proteins the problem does not exist, since the side chains may be set to the outside of the structure. However, for larger proteins, especially for proteins with beta sheets, the accuracy is significantly lower than the one obtained for the backbone only tests.

UniProt: the Universal Protein knowledgebase. Nucleic Acids Research 32, D115–D119 (2004) 17. : Induction of decision trees. Machine Learning 1(1), 81–106 (1986) 18. 5: Programs for Machine Learning. Morgan Kaufmann, San Francisco (1993) 19. : Fast effective rule induction. In: Proceedings of the Twelfth International Conference on Machine Learning, pp. 115–123 (1995) 20. : An Introduction to Support Vector Machines and other kernel-based learning methods. Cambridge University Press, Cambridge (2000) 21.

Biophysical Journal 5(6), 909 (1965) 17. : An efficient clash detection method for molecular structures. Technical Report 21, INESC-ID (August 2007) Top-Down Hierarchical Ensembles of Classifiers for Predicting G-Protein-Coupled-Receptor Functions Eduardo P. Costa1 , Ana C. F. Carvalho1 , and Alex A. Freitas3 3 1 Depto. uk Abstract. Despite the recent advances in Molecular Biology, the function of a large amount of proteins is still unknown. An approach that can be used in the prediction of a protein function consists of searching against secondary databases, also known as signature databases.

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Advances in Bioinformatics and Computational Biology: Third Brazilian Symposium on Bioinformatics, BSB 2008, Santo André, Brazil, August 28-30, 2008. Proceedings by Roberto T. Alves, Myriam R. Delgado, Alex A. Freitas (auth.), Ana L. C. Bazzan, Mark Craven, Natália F. Martins (eds.)


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