|The airway epithelium represents a critical component of the human lung that helps orchestrate defences against inhaled substances including air pollution, allergens, bacteria, and viruses. To manage these continuous insults, the airway epithelium has evolved to be a multi-functional barrier tissue with mechanical and immunological impedances that protect the lungs. In health, these coordinated functions can ensure that exposures to harmful substances are controlled to limit damage to the host, while in disease, a dysfunction in any capacity of the respiratory mucosa may lead to development or exacerbation of acute and chronic respiratory diseases. It is therefore important to understand the mechanisms that regulate respiratory mucosa function and how various stimuli may alter host defences. Using a bioinformatic approach focused primarily on transcriptomic data, this thesis presents analyses of three prevalent inhaled particulates: tobacco smoke, cannabis smoke, and respiratory viruses. I first characterize the ATP-binding cassette (ABC) transporter gene family, a relatively unexplored contributor to respiratory mucosa biology, in the context of both tobacco smoke exposure and viral infection. I then describe my direct comparison of the effects of cannabis and tobacco smoke exposure on lung health, uncovering striking similarities relating to functional consequences, response to combination treatment, and relationship to chronic lung disease that may inform future public health policies and individual user practices. Finally, I detail how, as part of the global effort to research the novel SARS-CoV-2 virus, I obtained results suggesting an alternate model of coronavirus-host cell invasion via ACE2-independent pathways and explore the mechanisms of the host immune response induced upon viral entry, advancing the field as it grapples with the COVID-19 pandemic. Bioinformatics coupled with large-scale data collection efforts around the world have provided a wealth of knowledge and new opportunities for biologists, including those studying respiratory medicine. Advancements in sequencing technologies and computational techniques have made possible the high-throughput analyses required to characterize the myriad changes that occur in the lungs upon exposure to various stimuli. Interdisciplinary "multi-omic" research is quickly positioning itself as a necessity for novel discoveries from within such large biological data sets. As researchers begin to adapt their experimental designs and incorporate new techniques, our collective understanding of the human airway will expand dramatically and result in increased quality of patient care and decreased global health burden. Thus, the studies presented here provide examples of how bioinformatics is essential for the advancement of the respiratory biology field.