Background: Boolean network (BN) modeling is a commonly used method for constructing gene regulatory networks from time series microarray data. However, its major drawback is that...
Abstract. We present an approach to inferring probabilistic models of generegulatory networks that is intended to provide a more mechanistic representation of transcriptional regul...
Networks are becoming a unifying framework for modeling complex systems and network inference problems are frequently encountered in many fields. Here, I develop and apply a gener...
We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
Background: The evolution of high throughput technologies that measure gene expression levels has created a data base for inferring GRNs (a process also known as reverse engineeri...