1. N.R. Aggarwal, L.S. King, F.R. D’Alessio, Diverse Macrophage Populations Mediate Acute Lung Inflammation and Resolution, American Journal of Physiology-Lung Cellular and Molecular Physiology 306 (8) (2014) L709–L725, ISSN 1040–0605, DOI: 10.1152/ajplung.00341.2013, http://www.physiology.org/doi/abs/10.1152/ajplung.00341.2013.
2. P. Aghasafari, I. Bin M. Ibrahim, R. Pidaparti, Strain-induced inflammation in pulmonary alveolar tissue due to mechanical ventilation, Biomechanics and Modeling in Mechanobiology 16 (4) (2017) 1103–1118, ISSN 1617–7940, DOI: 10.1007/s10237-017-0879-5, doi: 10.1007/s10237-017-0879-5.
3. K.J. Archer, R.V. Kimes, Empirical characterization of random forest variable importance measures, Computational Statistics & Data Analysis 52 (4) (2008) 2249–2260, ISSN 0167–9473, DOI: 10.1016/j.csda.2007.08.015, http://www.sciencedirect.com/science/article/pii/S0167947307003076.
4. J.H.T. Bates, C.G. Irvin, Time dependence of recruitment and derecruitment in the lung: a theoretical model, Journal of Applied Physiology 93 (2) (2002) 705–713, ISSN 8750–7587, DOI: 10.1152/japplphysiol.01274.2001, https://journals.physiology.org/doi/full/10.1152/japplphysiol.01274.2001, publisher: American Physiological Society.
5. Controlling the false discovery rate: a practical and powerful approach to multiple testing;Benjamini;Journal of the Royal statistical society: series B (Methodological),1995