Budding Brain

Budding Brain

Mathematics is used to illuminate the world around us by describing what we see through various models. Models can range from simple linear models of gravity and line weaver Burk to complex models such as models of storms. Simple models are easy to use but lack the accuracy in prediction that more complex model provide. The difference between this dynamic model and statistical model are descriptive while dynamic model are predictive. Descriptive model make sense of data and predictive model use the data you have to make prediction. This research seeks to uncover cross disciplinary nature of dynamic model and modeling. One of the models describes transcriptional regulatory network of yeast cells while the other models chaos and possible applications to artificial neural networks such as super computers and natural neural network such as brain mapping. In order to create simplified state some assumption are made for this data of these models. The model for the transcriptional yeast regulatory network is simplified stochastic differential equation model. The model for chaos is uses the three dimensional ordinary differential equation. The stochastic model is used to extract useful information from microarrays. The three dimensional ordinary differential equation models use the data from simple neural network to predict the behavior of more complex neural network.