The variety of models illustrated here provide a statistically reasonable fit to the overall breast cancer morbidity data considered, but they have very different shapes in the low-exposure region, resulting in very different EC01 estimates.
The simulation model approach illustrated here could be used to address related questions in a broader set of disparities in domains of disease prevention, early detection, and disease treatment.
Typical results generated by this model are illustrated here for a Carbon T-300/Bismaleimide material system.
The present study revealed the molecular basis for SMAD4-dependent and -independent differences in PDAC tumor biology with the aim of identifying the subset of patients likely to respond to therapies targeting the TGF-β or EGFR signaling pathways The use of model system illustrated here may help to identify additional nodes of therapeutic intervention in PDAC patients devoid of SMAD4.
The agent-based modelling paradigm illustrated here provides a useful technique for understanding many aspects of biological systems.
While it is possible to extend the modeling formalism illustrated here in these and other directions, the additional combinatorial complexity would make surveys of multi-component networks computationally challenging.
The modelling tools illustrated here could easily be adapted for other Ebola outbreaks, and highlight the benefits of having data on likely source of infection and time of onset, hospitalisation and outcome for each patient.
The combination of image quantification, model building, and computer simulation is illustrated here using the example of diffusion in the endoplasmic reticulum.
The model is successfully illustrated here with two brief case examples: effects of PM and blood lead levels.
The functional modeling of differentially expressed genes illustrated here has identified long-suspected pathologic hubs centering on TNFα and IFNγ, and, in addition, a previously unknown (but biologically sensible) hub for proteins such as VIL2.
