The immune system is composed of different cell types that work in a coordinated manner to maintain the integrity of the organism in situations of threats or danger. Dendritic cells (DC) act as sentinels in peripheral tissue and mucosal interfaces where they integrate a diversity of danger- and inflammation-associated stimuli, then migrate to secondary lymphoid organs, and instruct naïve CD4 T cells to differentiate into the appropriate effector T cells. Hence, they play a critical role in linking innate to adaptive immunity. Three important levels of complexity characterize the DC system: 1) DC integrate multiple stimuli within complex inflammatory microenvironments, 2) these signals induce a complex output response and modify the global state of DC (environmental plasticity), 3) DC exist in different subsets generated by distinct differentiation pathways (evolutionary selection). In this proposal, we use cellular and molecular immunology combined to computational biology and modeling to study these properties at the large-scale level, and understand their interdependence in controlling DC biology. We ask the following specific questions: WP1: How DC subsets integrate combinations of stimuli at the large-scale level; WP2: How single and multiple stimuli modify DC state over time (dynamic modeling); WP3: How the DC global state influences response to a given stimulus. These questions will be addressed using a data-driven strategy combining global unsupervised exploratory analysis, gene-by-gene analysis and modeling, experimental validation of testable hypothesis. Through this systems level integrative approach, we will dissect the complexity of DC reciprocal interactions with their complex microenvironment, and hope to unravel novel mechanisms and concepts determining DC function.