Fabrizio F. Borelli

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Gene regulatory networks (GRN) inference is an important bioinformatics problem in which the gene interactions need to be deduced from gene expression data, such as microarray data. Feature selection methods can be applied to this problem. A feature selection technique is composed by two parts: a search algorithm and a criterion function. Among the search(More)
The Internet of Things (IoT) application development is a complex task that requires a wide range of expertise. Currently, the IoT community lacks a development toolkit that enables inexperienced developers to develop IoT prototypes rapidly. Filling this gap, we propose a development toolkit based on a model-driven approach, called IoT Link. IoT Link allows(More)
Gene regulatory networks (GRN) inference is an important bioinformatics problem in which the gene interactions need to be deduced from gene expression data, such as microarray data. Feature selection methods can be applied to this problem. A feature selection technique is composed by two parts: a search algorithm and a criterion function. Among the search(More)
The importance of energy in our society has been growing drastically but still, public buildings are very inefficient when it comes to managing energy. Current management systems are usually designed for automating lighting and HVAC. We see the potential of using IoT in this scenario but unfortunately developing context-aware IoT systems still takes(More)
Gene regulatory networks inference is one of the crucial problems of the Systems Biology field. It is still an open problem, mainly because of its high dimensionality (thousands of genes) with a limited number of samples (dozens), making it difficult to estimate dependencies among genes. Besides the estimation problem, another important hindrance is the(More)
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