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Roberto Serra
Researcher at University of Modena and Reggio Emilia
Publications - 199
Citations - 2707
Roberto Serra is an academic researcher from University of Modena and Reggio Emilia. The author has contributed to research in topics: Boolean network & Protocell. The author has an hindex of 26, co-authored 194 publications receiving 2483 citations. Previous affiliations of Roberto Serra include Gazeta Tema & University of Amsterdam.
Papers
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Journal ArticleDOI
An empirical method for modelling and simulating some complex macroscopic phenomena by cellular automata
TL;DR: An empirical method applied with interesting results in modelling and simulating some complex macroscopic phenomena seems to satisfy the applicability conditions of such an empirical method.
Journal ArticleDOI
Genetic network models and statistical properties of gene expression data in knock-out experiments.
TL;DR: Findings suggest that the distributions of avalanches and susceptibilities of the RBN models are close to those observed in actual experiments performed with S. cerevisiae, and might be "generic" properties, common to a wide range of genetic models and real genetic networks.
Journal ArticleDOI
Why a simple model of genetic regulatory networks describes the distribution of avalanches in gene expression data.
TL;DR: The reason why a simple random Boolean network model, with two input connections per node, can describe with a good approximation the distribution of perturbations in gene expression levels induced by the knock-out of single genes in Saccharomyces cerevisiae is addressed.
Book
Complex systems and cognitive processes
Roberto Serra,G. Zanarini +1 more
TL;DR: This book shows that the science of complex systems, which stresses the importance of self-organizing processes, can make a decisive contribution to solving many problems in artificial intelligence.
Journal ArticleDOI
On the dynamics of random Boolean networks subject to noise: attractors, ergodic sets and cell types.
TL;DR: It is shown that the Threshold Ergodic Sets so defined are robust with respect to noise and, at the same time, that they do not suffer from a major drawback of ergodic sets.