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Development of powerful new high-throughput technologies for probing the transcriptome, proteome, and metabolome is driving the rapid acquisition of information on the function of molecular systems. One of the greatest challenges that we now confront is to understand how behavior at the level of genome, proteome, and metabolome shapes physiological function at the level of cell, tissue and organ in both health and disease. Because of the inherent complexity of biological systems, the development, analysis, and validation of integrative computational models based directly on experimental data is necessary to achieve thisunderstanding. This approach,knownassystemsbiology,integratescomputationaland experimental approaches through iterative development of mathematical models and experimental validation and testing. The combination of these approaches allows for a mechanistic understanding of the function of complex biological systems in health, and their dysfunction in disease. In 2006, the National Heart, Lung, and Blood Institute (NHLBI) announced the Exploratory Program in Systems Biology, followed in 2010 by the NHLBI Systems Biology Collaborations. The goal of these programs is to support collaborative teams of investigators in using experimental and computational strategies to integrate the component parts of biological networks and pathways into computational models that are based firmly on and validated using experimental data. These validated models are then applied to gain insights into the mechanisms of altered system function in disease, to generate novel hypotheses regarding these mechanisms that can be tested experimentally, and to then use the results of experiments to refine the models. This Research Topic is comprised of articles by researchers funded by this NHLBI program. One set of publications focus on lung function in health and disease. Lauzon et al. (2012) present a multi-scale model of lung function spanning molecular (force production by actin-myosin proteins), cellular (regulation of force production by calcium signaling), tissue (smooth muscle contraction coupled with the biomechanics of airway narrowing), and organ scales (mechanical lung impedance). The model provides a new tool for investigating airway hyper responsiveness in the setting of asthma and other lung diseases. O’Connor et al. (2012) present a closed-loop model of neural control of breathing that includes a neural network model of the respiratory pattern generator that drives a systems-level model of lung contraction with feedback to the respiratory pattern generator driven by mechano- and baro-receptor reflexes. The model provides a framework for studying cough disorders. Segers et al. (2012) present results from an experimental study aimed at identifying the role of different neuronal populations in regulating fricative cough. Finally, Fallahi-Sichani et al. (2012) present a multi-scale model of the lung immune response to Mycobacterium tuberculosis and use the model to examine the ways in which the NF-kB signaling pathway regulates inflammatory responses. Another set of publications focus on blood disease. Dick et al. (2012) develop a multi-scale model of acute inflammatory disease, such as sepsis, that describes baro-, chemo-, and cytokine-reflex control of cardio-pulmonary function mediated by the nucleus tractus solitarius (nTS). They present the model-motivated hypothesis that the dis-regulation of cardio-respiratory patterns in the setting of sepsis results from expression of cytokines in the nTS. Goldman et al. (2012) develop models of the erythrocyte signaling pathways that control ATP release as a function of hemoglobin oxygen saturation. These models provide a new framework for studying regulation of microvascular perfusion distribution. Diamond et al. (2013) resent a modeling approach that combines fluiddynamicssimulationofbloodflowinthepresenceofadeveloping

Systems biology approaches to understanding the cause and treatment of heart, lung, blood, and sleep disorders