This volume tackles a variety of biological and medical questions using mathematical models to understand complex system dynamics. Working in collaborative teams of six, each with a senior research mentor, researchers developed new mathematical models to address questions in a range of application areas. Topics include retinal degeneration, biopolymer dynamics, the topological structure of DNA, ensemble analysis, multidrug-resistant organisms, tumor growth modeling, and geospatial modeling of malaria. The work is the result of newly formed collaborative groups begun during the Collaborative Workshop for Women in Mathematical Biology hosted by the Institute of Pure and Applied Mathematics at UCLA in June 2019. Previous workshops in this series have occurred at IMA, NIMBioS, and MBI.

This volume tackles a variety of biological and medical questions using mathematical models to understand complex system dynamics. Working in collaborative teams of six, each with a senior research mentor, researchers developed new mathematical models to address questions in a range of application areas. Topics include retinal degeneration, biopolymer dynamics, the topological structure of DNA, ensemble analysis, multidrug-resistant organisms, tumor growth modeling, and geospatial modeling of malaria. The work is the result of newly formed collaborative groups begun during the Collaborative Workshop for Women in Mathematical Biology hosted by the Institute of Pure and Applied Mathematics at UCLA in June 2019. Previous workshops in this series have occurred at IMA, NIMBioS, and MBI.

This work is an investigation of particle deposition and air flow in the human lung. In particular we are interested in how the motion of particulate matter and air is affected by the presence of lung disease. Patients with compromised lung function are more sensitive to air pollution; understanding the extent of that sensitivity can lead to more effective air quality standards. Also, understanding of air flow and particle trajectories could lead to the development of better aerosol drugs to treat the lung diseases. Computational flow models are used to model two different airway diseases, chronic obstructive pulmonary disease (COPD) and bronchial tumors. The presence of disease in the lung has a large effect both on global deposition patterns and on localized airflow patterns. This indicates the need for different protocols regarding susceptibility of people to airborne pollutants that take into account lung disease. It also suggests that treatment should account for changes in airflow in the diseased lung.