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Despite great advances in discovering cancer molecular profiles, the proper application of microarray technology to routine clinical diagnostics is still a challenge. Current practices in the classification of microarrays' data show two main limitations: the reliability of the training data sets used to build the classifiers, and the classifiers'(More)
A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for(More)
Porto, the institutional repository of the Politecnico di Torino, is provided by the University Library and the IT-Services. The aim is to enable open access to all the world. Please share with us how this access benefits you. Your story matters. obtained for all other uses, in any current or future media, including reprinting/republishing this material for(More)
Boolean Networks are emerging as a simple yet powerful formalism to model and study Gene Regulatory Networks. Nevertheless, the most widely used Boolean Network-based models do not include any post-transcriptional regulation mechanism. In this paper we discuss how the post-transcriptional regulation mechanism mediated by miRNAs can be included in a Boolean(More)
The use of Bioinformatic tools in routine clinical diagnostics is still facing a number of issues. The more complex and advanced bioinformatic tools become, the more performance is required by the computing platforms. Unfortunately, the cost of parallel computing platforms is usually prohibitive for both public and small private medical practices. This(More)
Many new therapeutic techniques depend not only on the knowledge of the molecules participating in the biological phenomena but also their biochemical function. Advancements in prediction of new proteins are immense if compared with the annotation of functionally unknown proteins. To accelerate the personalized medicine effort, computational techniques(More)
The continuing discovery of new functions and classes of small non-coding RNAs is suggesting the presence of regulatory mechanisms far more complex than the ones identified so far. In our computational analysis of a large set of public available databases, we found statistical evidence of an inter-pathway regulatory motif, not previously described, that(More)
This paper proposes a new and very flexible data model, called gene expression graph (GEG), for genes expression analysis and classification. Three features differentiate GEGs from other available microarray data representation structures: (i) the memory occupation of a GEG is independent of the number of samples used to built it; (ii) a GEG more clearly(More)
Networks Biology allows the study of complex interactions between biological systems using formal, well structured, and computationally friendly models. Several different network models can be created, depending on the type of interactions that need to be investigated. Gene Regulatory Networks (GRN) are an effective model commonly used to study the complex(More)
Keywords: MiRNA Gene regulatory networks Post-transcriptional regulation Boolean networks Complex systems Network analysis a b s t r a c t Gene regulatory networks (GRNs) model some of the mechanisms that regulate gene expression. Among the computational approaches available to model and study GNRs, Boolean network (BN) emerged as very successful to better(More)