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Protein structures allow for a straightforward representation in terms of graph theory being the nodes the aminoacid residues and the edges the scoring of a spatial contact between the node pairs. Such a representation allows for a direct use in the realm of protein science of the vast repertoire of graph invariants developed in the analysis of complex networks. In this work we give a general overview of the protein as networks paradigm with a special emphasis on haemoglobin where the most important features of protein systems like allostery, protein-protein contacts and differential effect of mutations were demonstrated to be amenable to a graph theory oriented translation.

This paper deals with a new approach to multi robot localization. An Interlaced extended Kalman filter is shown to be a good solution to the problem of estimating the pose of a team of robots with a fully decentralized algorithm. Moreover, it is feasible to dynamically "correct" the estimation autonomously evaluated by each single robot, updating this quantity anytime two robots randomly come across. The algorithm combines the robustness of a full state EKF with the simplicity of its interlaced implementation. It does not need global supervision, and allows a large flexibility in using exteroceptive sensors. The paper presents some simulations to show the feasibility of the approach considering a set of robots equipped with different combinations of sensors and with wireless communication devices able to support data exchange when they are sufficiently clos