Kristin R. Swanson

This study examines the spatiotemporal myeloid response to chemotherapy in glioblastoma using multiple models, showing chemotherapy-induced genotoxic stress and inflammatory remodeling in myeloid cells.

This paper develops a mathematical model of GBM tumor growth and evaluates BMP4 as a differentiation therapy through virtual clinical trials, finding that continuous BMP4 delivery during radiotherapy is more effective than a single dose.

This study computes morphological metrics from MRI scans of glioblastoma patients to correlate with survival outcomes, finding significant associations with overall survival.

The paper develops a Bayesian framework to quantify uncertainty in a glioblastoma treatment response metric, showing robustness across a range of cutoff values for predicting time to progression.

The paper introduces the ENDURES consortium to study extreme survivors of glioblastoma by integrating clinical data and creating patient-specific tumor models.

This paper introduces a simulation-based metric, Days Gained, to assess glioblastoma response to therapy using MRI-derived growth models.

The paper introduces a hybrid method to estimate parameters in agent-based models using glioblastoma data to improve model calibration.

The paper introduces MultiCellDS, a standard and community-driven initiative for sharing multicellular data to enhance research in cell biology.

The paper introduces MultiCellDS, a standard for multicellular data curation, and presents MultiCellDB as a database to store associated data, enhancing data sharing and utility in biological and clinical research.

The paper adapts a reaction-diffusion model to study PDGF-driven glioma recruitment in experimental models, examining factors influencing cell recruitment and tumor characteristics.