Evolutionary Biogeography: An Integrative Approach

EGIA - Evolutionary Optimisation of Gene Regulatory Networks, an Integrative Approach

Quantitative modelling of gene regulatory networks (GRNs) is still limited by data issues such as noise and the restricted length of available time series, creating an under-determination problem. However, large amounts of other types of biological data and knowledge are available, such as knockout experiments, annotations and so on, and it has been postulated that integration of these can impr...

An Approach to Reducing Overfitting in FCM with Evolutionary Optimization

Fuzzy clustering methods are conveniently employed in constructing a fuzzy model of a system, but they need to tune some parameters. In this research, FCM is chosen for fuzzy clustering. Parameters such as the number of clusters and the value of fuzzifier significantly influence the extent of generalization of the fuzzy model. These two parameters require tuning to reduce the overfitting in the...

towards an integrative approach to trauma study

Hybrid biogeography-based evolutionary algorithms

Hybrid evolutionary algorithms (EAs) are effective optimization methods that combine multiple EAs. We propose several hybrid EAs by combining some recently-developed EAs with a biogeography-based hybridization strategy. We test our hybrid EAs on the continuous optimization benchmarks from the 2013 Congress on Evolutionary Computation (CEC) and on some real-world traveling salesman problems. The...

Behavioral Neurobiology. An integrative approach.

Günther Zupanc's Behavioral Neurobiology is primarily a neuroethological textbook that is based on his experiences teaching both beginners and advanced level students in neurobiology. He has produced a book that students find fascinating and clearly written. This book is not intended as a comprehensive survey of behavioral neurobiology, but it does stimulate student interest and understanding. ...