In the last 10 years, the availability of time-resolved data in many fields has led to the extension of the field of networks to the study of temporal networks. In a static network, nodes represent elements of the system and links between nodes encode the fact that an interaction exists between the corresponding elements. Links are then fixed and no information on the timing of these interactions is available. In a temporal network instead, links are replaced by temporal series of interactions, each with its starting time and duration. Taking into account temporality has important consequences in terms of analysis and modelling. Finding relevant structures in temporal networks is, in particular, a challenging task, and I will present two methods recently developed: the extraction of a backbone of significant ties on the one hand, and the temporal core decomposition, which allows us to identify dense structures, together with their temporal span.