This research line of the unit aims to develop efficient and scalable algorithms for the analysis of biological and genomic data, in order to rapidly gather high-quality knowledge in various fields. Among these we can mention the extraction of simple and structural motifs, the identification and extraction of tandem repeat sequences, the analysis of gene expression data from microarrays, the analysis of haplotypes, the analysis of metabolic networks and the classification of diseases. through gene expression profiles.
Another line of research focuses on the various phases of RNA sequencing to propose new algorithmic approaches. This is done in particular through data preprocessing and normalization techniques, algorithms for differential analysis and methods for the creation of specific biomarker panels.
We also work on computational solutions and models for the characterization of the functional role of microRNAs in cardiac pathologies and as circulating non-invasive biomarkers for the therapeutic monitoring of cancer or diabetic patients.
The aim of this research activity is to improve urban mobility and reduce its environmental and economic impact. For this reason we study the benefits produced by the so-called “sharing economy” in urban transport, taking into account the sharing of journeys and/or vehicles and the impact of micro-mobility and self-driving vehicles on city infrastructure.
We also tackle the problem of efficiently managing fleets of vehicles, both from the point of view of the impact of a possible electrification, and regarding the optimization of ride sharing algorithms. The “human factor” is also taken into consideration from different perspectives. These include addressing the problems associated with pedestrian navigation in urban contexts, studying characterizations of “driver behavior”, and evaluating the impact of the application of privacy (information location) on shared mobility, both in terms of efficiency and quality of service.
We study the fundamental properties of wireless networks, such as connectivity, radio interference, network life time, spatial distribution of nodes in the presence of mobility, propagation of safety-critical messages in vehicular networks. In particular, we focus on protocols for new generation wireless networks, through the analysis of mechanisms for device-to-device communications in cellular networks and the synthesis of scalable and efficient algorithms for the allocation of resources in systems with ultra-reliable low latency communications (URLLC), with applications within the context of the Internet of Things and Industry 4.0.
This line of research shares features with both that relating to wireless networks and that regarding smart mobility. It foresees analytical study on the spread of epidemic phenomena in complex networks, with particular attention to the effectiveness and impact of the main containment strategies on the operation of the network itself.
In particular, we study innovative wireless systems capable of monitoring traffic on an urban scale and proposing effective multimodal commuting strategies, which take into account both environmental aspects and recent restrictions due to the pandemic situation.
Within this context, the activity is mainly basic research. Some of the topics recently studied are the following: analysis and synthesis of algorithms for resolving large-scale linear systems; study of the regularizing properties of iterative methods for ill-conditioned problems with application to image reconstruction; study of “fast” and “superfast” methods for the resolution of linear systems with structure; synthesis of algorithms for the non-negative factorization of matrices (NMF).
The scientific dissemination mainly concerns topics of logic, game theory, cryptography and algorithms. This activity includes presentations in schools and the publication of books and articles in educational journals.