Background: Despite recent algorithmic and conceptual progress, the stoichiometric network analysis of large metabolic models remains a computationally challenging problem. Result...
Predicting timing behavior is key to efficient embedded real-time system design and verification. Especially memory accesses and co-processor calls over shared communication net...
Background: Several supervised and unsupervised learning tools are available to classify functional genomics data. However, relatively less attention has been given to exploratory...
Bayesian MLP neural networks are a flexible tool in complex nonlinear problems. The approach is complicated by need to evaluate integrals over high-dimensional probability distri...
It has been proposed that chaos can serve as a reservoir providing an infinite number of dynamical states [1, 2, 3, 4, 5]. These can be interpreted as different behaviors, search a...