Advances in Bioinformatics and Computational Biology: Second by Marie-France Sagot, Maria Emilia M.T. Walter

By Marie-France Sagot, Maria Emilia M.T. Walter

This booklet constitutes the refereed complaints of the second one Brazilian Symposium on Bioinformatics, BSB 2007, held in Angra dos Reis, Brazil, in August 2007; co-located with IWGD 2007, the foreign Workshop on Genomic Databases.

The thirteen revised complete papers and six revised prolonged abstracts have been rigorously reviewed and chosen from 60 submissions. The papers handle a wide variety of present subject matters in computationl biology and bioinformatics that includes unique learn in machine technology, arithmetic and records in addition to in molecular biology, biochemistry, genetics, drugs, microbiology and different lifestyles sciences.

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Extra resources for Advances in Bioinformatics and Computational Biology: Second Brazilian Symposium on Bioinformatics, BSB 2007, Angra dos Reis, Brazil, August 29-31,

Sample text

The overall deviation of a partition measures the overall summed distances between objects and their corresponding cluster center. This measure is strongly biased towards spherically shaped clusters and improves with the increase in the number of clusters. The connectivity reflects how often neighboring objects have been placed in the same cluster. It improves with the decrease in the number of clusters. The connectivity is able to detect arbitrarily shaped clusters, but it is not robust to deal with overlapping clusters.

To begin in this direction, here we focus our experiments in the planted motif problem defined in [14] and compare results with Gibbs Sampler [11]. In [5], a standard GA is proposed to deal with the problem, here the representation is given by a vector of initial positions, corresponding to each occurrence of the motif. The results are compared with the ones produced by Gibbs Sampler [11], BioProspector [13], MEME [1], Consensus [8] and AlignACE [16] on a small set of real cases with competitive results.

It is clear that this size increases exponentially with the number of sequences N . If we choose the motif based representation the search space size is still exponential, 4l , although independent of the number and length of 28 G. A. Brizuela sequences, it grows exponentially with the motif length. However, in the planted motif problems the number and length of sequences is a real issue, for details see [4]. Notice that the difference in size of the search spaces will probably require a bigger population size for the position based encoding.

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