Parallel Hematopoietic Stem Cell Division Rate Estimation Using an Agent-Based Model on the Grid

In previous work we presented supportive computational analysis on newly found biological evidence which indicates the existence of a dormant Hematopoietic Stem Cell (HSC) population. Through extensive modelling of experimental DNA label-retaining cell data we showed that an ordinary differential equation (ODE) model can successfully capture a heterogeneous HSC population structure. The ODE model's analytical tractability made it especially suitable for parameter estimation in contrast to an earlier agent-based model we developed on a related but independent Bromodeoxyuridine (BrdU) dataset. For this current study we explore the predictive power of the same agent-based model on the larger more elaborate BrdU dataset by comparing the BrdU detection threshold (BDT) estimates of both the ODE (continuous BDT implementation) and agent-based (discrete BDT implementation) models. We therefore re-estimate the HSC division parameters using the agent-based model which entailed a brute-force search approach. In order to cover a worthwhile region of the parameter hyperspace within a reasonable amount of time we executed our search algorithm in parallel over the EGEE Grid environment. Our results indicate that the agent-based model more or less supports the same conclusions as the ODE model. However, actual cell division rate estimates as well as model prediction differ slightly for the same set of parameters. The estimates for the dormant HSC proportion and BDT, on the other hand, are in strong agreement with the ODE estimates. For the BDT in particular, this is an encouraging result as the two models have a very different approach in their implementation of the BDT.