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

This publication constitutes the refereed court cases 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 tackle a vast diversity of present themes in computational biology and bioinformatics that includes unique study in laptop technology, arithmetic and statistics in addition to in molecular biology, biochemistry, genetics, medication, microbiology and different lifestyles sciences.

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

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The type of model used and the threshold limit will have to be chosen according to the type of proteins (specially their secondary structure and size) and the search algorithm. For a search algorithm, with no specific information, a four states model, specially a generic one like the C model, with a side chain threshold An Evaluation of the Impact of Side Chain Positioning on the Accuracy 33 of 1% will probably have best results because of the increase in the size of the searched space. If the protein is small, there are fewer possible conformations, and more detailed models can be found using more rotamers or even using the six states model.

Consequently, although some conflicts may now be avoidable, the cost of the extra tests might not allow for the same number of conformations to be tested. This increase of time for each side chain positioning will have an even greater impact in an ab-initio search algorithm, since no exact measure like the RMSD exists. Without an exact measure, the number of wrong conformations searched will be much greater and the increased computational cost of the enlarged library will further decrease the performance.

To set the side chains we used a maximum number of possible alterations (see section 2) equal to the number of amino acids divided by 10. We have first tried the algorithm presented by Park and Levitt [5] for testing discrete state models. The algorithm does a simple beam search using the RMSD distance as the scoring function. In a beam search, n states are saved at any given time. Considering that there are m choices in an m state discrete model, the algorithm starts by testing the first m choices.

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