Data belonging to the publication "Predicted effects of patient variability and Notch signaling on in situ vascular tissue engineering"

This study adopts a previously published multiscale computational framework for arterial growth and remodeling and adapts it for applications in in situ vascular tissue engineering. The framework consists of a constrained mixture model, capturing the mechanics and turnover of arterial constituents, and a cell-cell signaling model, describing Notch signaling dynamics among vascular smooth muscle cells. With the model, we computationally explored potential sources of tissue engineered vascular graft (TEVG) variability and effects of manipulating Notch, a key vascular signaling pathway. We simulated the evolution of a TEVG from a degradable scaffold under varying patient-specific conditions.

This dataset contains the computational codes for the multiscale framework and the raw data from the simulations.