Code Repositories
Here you will find links to the code repositories for some of the publications by researchers at Simpson Querrey Lung Institute for Translational Science (SQLIFTS).
General
- NU SCRIPT Study on GitHub
- NU Pulmonary on GitHub
Specific Publications
- Grant RA, Morales-Nebreda L, Markov NS, et al. Circuits between infected macrophages and T cells in SARS-CoV-2 pneumonia. Nature. 2021; 590(7847):635-641. GitHub: NUPulmonary / 2020_Grant.
- Stoeger T, et al. Aging is associated with a systemic length-associated transcriptome imbalance. Nature Aging. 2022; 2(12):1191-1206. GitHub: NUPulmonary / stoeger_et_al_2022_transcriptome_imbalance.
- Gao CA, Markov NS, Stoeger T, et al. Machine learning links unresolving secondary pneumonia to mortality in patients with severe pneumonia, including COVID-19. Journal of Clinical Investigation. 2203; 133(12):e170682. GitHub: NUSCRIPT / CarpeDiem.
- Grant RA, Poor TA, et al. Prolonged exposure to lung-derived cytokines is associated with activation of microglia in patients with COVID-19. JCI Insight. 2024; 9(8):e178859. GitHub: NUPulmonary / 2023_Grant_Poor.
- Bailey JI, Puritz CH, Senkow KJ, et al. Profibrotic monocyte-derived alveolar macrophages are expanded in patients with persistent respiratory symptoms and radiographic abnormalities after COVID-19. Nature Immunology. 2024; 25(11):2097-2109. GitHub: / Bailey_Puritz_Senkow_RPRA_2024.
- Markov NS, et al. Distinctive evolution of alveolar T cell responses is associated with clinical outcomes in unvaccinated patients with SARS-CoV-2 pneumonia. Nature Immunology. 2024; 25(9):1607-1622. GitHub: / 2024_Markov_Ren_Senkow.
- Fenske SW, Peltekian A, et al. Developing and validating a machine learning model to predict successful next-day extubation in the ICU (preprint).