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...
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...
Background: Inferring a gene regulatory network (GRN) from high throughput biological data is often an under-determined problem and is a challenging task due to the following reas...
Yuji Zhang, Jianhua Xuan, Benildo de los Reyes, Ro...