Giuliano Armano

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Due to the strict relation between protein function and structure, the prediction of protein 3D-structure has become one of the most important tasks in bioinformatics and proteomics. In fact, notwithstanding the increase of experimental data on protein structures available in public databases, the gap between known sequences and known tertiary structures is(More)
When a sample belongs to more than one label from a set of available classes, the classification problem (known as multi-label classification) turns to be more complicated. Text data, widely available nowadays in the world wide web, is an obvious instance example of such a task. This paper presents a new method for multi-label text categorization created by(More)
The adoption of agent technologies and multi-agent systems constitutes an emerging area in bioinformatics. In this article, we report on the activity of the Working Group on Agents in Bioinformatics (BIOAGENTS) founded during the first AgentLink III Technical Forum meeting on the 2nd of July, 2004, in Rome. The meeting provided an opportunity for seeding(More)
Contextual advertising and automatic recommendation are emerging fields deeply studied by researchers in information retrieval. So far, these fields have been separately investigated and several solutions have been independently proposed in the literature. Nevertheless, in our view, there are common issues that drive us to think that systems devised to(More)
In this paper, a generic architecture, designed to support the implementation of applications aimed at managing information among different and heterogeneous sources, is presented. Information is filtered and organized according to personal interests explicitly stated by the user. User profiles are improved and refined throughout time by suitable adaptation(More)
—Clustering is a popular data analysis and data mining technique. Among different proposed methods, k-means is an efficient clustering technique to cluster datasets, but this method highly depends on the initial state and usually converges to local optimum solution. This paper takes the advantage of a novel evolutionary algorithm, called artificial bee(More)
Single Nucleotide Polymorphism (SNP) genotyping analysis is very susceptible to SNPs chromosomal position errors. As it is known, SNPs mapping data are provided along the SNP arrays without any necessary information to assess in advance their accuracy. Moreover, these mapping data are related to a given build of a genome and need to be updated when a new(More)