Matteo Comin

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The construction of suffix tree for very long sequences is essential for many applications, and it plays a central role in the bioinformatic domain. With the advent of modern sequencing technologies, biological sequence databases have grown dramatically. Also the methodologies required to analyze these data have become everyday more complex, requiring fast(More)
The discovery of motifs in biosequences is frequently torn between the rigidity of the model on one hand and the abundance of candidates on the other hand. In particular, motifs that include wild cards or “don't cares” escalate exponentially with their number, and this gets only worse if a don't care is allowed to stretch up to some prescribed(More)
MOTIVATION The discovery of motifs in biosequences is frequently torn between the rigidity of the model on the one hand and the abundance of candidates on the other. In particular, the variety of motifs described by strings that include 'don't care' (dot) patterns escalates exponentially with the length of the motif, and this gets only worse if a dot is(More)
Motif patterns of maximal saturation emerged originally in contexts of pattern discovery in biomolecular sequences and have recently proven a valuable notion also in the design of data compression schemes. Informally, a motif is a string of intermittently solid and wild characters that recurs more or less frequently in an input sequence or family of(More)
Bioinformatics applications manage complex biological data stored into distributed and often heterogeneous databases and require large computing power. Among these, protein structure comparison applications exhibit complex workflow structure, access different databases, require high computing power. Thus they could benefit of semantic modelling and Grid(More)
With the progress of modern sequencing technologies a large number of complete genomes are now available. Traditionally the comparison of two related genomes is carried out by sequence alignment. There are cases where these techniques cannot be applied, for example if two genomes do not share the same set of genes, or if they are not alignable to each other(More)
We present a new method for protein structure comparison that combines indexing and dynamic programming (DP). The method is based on simple geometric features of triplets of secondary structures of proteins. These features provide indexes to a hash table that allows fast retrieval of similarity information for a query protein. After the query protein is(More)
The automatic classification of protein sequences into families is of great help for the functional prediction and annotation of new proteins. In this article, we present a method called Irredundant Class that address the remote homology detection problem. The best performing methods that solve this problem are string kernels, that compute a similarity(More)
With the progress of modern sequencing technologies a number of complete genomes is now available. Traditional motif discovery tools cannot handle this massive amount of data, therefore the comparison of complete genomes can be carried out only with ad hoc methods. In this work we propose a distance function based on subword compositions, which extends the(More)
The classification of protein sequences using string algorithms provides valuable insights for protein function prediction. Several methods, based on a variety of different patterns, have been previously proposed. Almost all string-based approaches discover patterns that are not "independent, " and therefore the associated scores overcount, a multiple(More)