Auditory models are computational models which mimic the human auditory process by transforming acoustic signals into neural activity of simulated auditory nerve fibers (channels).
The development of three dimensional (3D) culture models which mimic that displayed in vivo can improve cancer biology studies and accelerate novel anticancer drug screening.
"Bag of (local visual) features" (BoF) models, which mimic and were inspired by "bag of words" approaches to natural language processing and information retrieval, have proven very successful for image categorization.
The development of well-defined three-dimensional (3D) in vitro models, which mimic ECM structures as found in vivo, have demonstrated the importance of cell-matrix bio-mechanics, the complex interactions between HSCs and hepatocytes and other non-parenchymal cells, and this to improve and promote liver cell-specific functions.
Thus, efforts to establish new cancer animal models which mimic heterogeneous patient populations might be even more challenging than initially realized [1], [4].
We present a computational toolbox for generating random biochemical network models which mimic real biochemical networks.
So far, models which mimic the human gastro-intestinal events have been derived from anatomical and enzymatic understanding and less so from, e.g., a fluid dynamics approach.
The resulting models, which mimicked some of the diversity of human noninvasive breast cancers in vivo, were used to show whether subtypes of human DCIS might contain distinct subpopulations of tumor-initiating cells.
These factors therefore appear to play a key role in the pathophysiology of gastric disease development and their importance should be investigated in animal models which mimic human gastric neoplasia.
Indeed, one of the major limitations to our knowledge of human neurological diseases resides partly in the limits inherent to animal models, which mimic some aspects of the human neurological disorder without reproducing its complexity arising from both genetic and environmental factors.
