In this work we present an improved evolutionary method for inferring S-system model of genetic networks from the time series data of gene expression. We employed Differential Ev...
Background: Modelling the time-related behaviour of biological systems is essential for understanding their dynamic responses to perturbations. In metabolic profiling studies, the...
Mattias Rantalainen, Olivier Cloarec, Timothy M. D...
ARIMA is a popular method to analyze stationary univariate time series data. There are usually three main stages to build an ARIMA model, including model identification, model est...
This paper reviews statistical methods for analyzing output data from computer simulations. Specifically, it focuses on the estimation of steady-state system parameters. The esti...
Previous methods of network anomaly detection have focused on defining a temporal model of what is "normal," and flagging the "abnormal" activity that does not...
Kevin M. Carter, Richard Lippmann, Stephen W. Boye...