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International audience; Permanent exhibitions in museums are the outcome of processes of construction of historical knowledge, which can occur both within or outside the museum. However, this particular type of historical narrative is somehow inconsistent with the possibility of integrating more recent academic work and it is physically limited when it comes to embrace the historical complexity and multilayered lives of objects. With examples taken both from art and science museums, we will seek to outline the problems and possible responses to curating history, especially when departing from a material culture approach or science studies at the same time as trying to integrate the public's voice. This paper is the second step in a project led by researchers from the EUI in Florence, the CHAM research centre in Lisbon and the University of Warwick which culminated with an international workshop in Florence in October 2017 (https://curatinghistory.wordpress.com/).

International audience; BACKGROUND: Protein-protein interaction (PPI) network analyses are highly valuable in deciphering and understanding the intricate organisation of cellular functions. Nevertheless, the majority of available protein-protein interaction networks are context-less, i.e. without any reference to the spatial, temporal or physiological conditions in which the interactions may occur. In this work, we are proposing a protocol to infer the most likely protein-protein interaction (PPI) network in human macrophages. RESULTS: We integrated the PPI dataset from the Agile Protein Interaction DataAnalyzer (APID) with different meta-data to infer a contextualized macrophage-specific interactome using a combination of statistical methods. The obtained interactome is enriched in experimentally verified interactions and in proteins involved in macrophage-related biological processes (i.e. immune response activation, regulation of apoptosis). As a case study, we used the contextualized interactome to highlight the cellular processes induced upon Mycobacterium tuberculosis infection. CONCLUSION: Our work confirms that contextualizing interactomes improves the biological significance of bioinformatic analyses. More specifically, studying such inferred network rather than focusing at the gene expression level only, is informative on the processes involved in the host response. Indeed, important immune features such as apoptosis are solely highlighted when the spotlight is on the protein interaction level.