Seeded Bayesian Networks: Constructing genetic networks from microarray data

Bayesian Inference of Genetic Regulatory Networks from Time Series Microarray Data Using Dynamic Bayesian Networks

Reverse engineering of genetic regulatory networks from time series microarray data are investigated. We propose a dynamic Bayesian networks (DBNs) modeling and a full Bayesian learning scheme. The proposed DBN directly models the continuous expression levels and also is associated with parameters that indicate the degree as well as the type of regulations. To learn the network from data, we pr...

Constructing Bayesian Network Models of Gene Expression Networks from Microarray Data

BNArray: an R package for constructing gene regulatory networks from microarray data by using Bayesian network

UNLABELLED BNArray is a systemized tool developed in R. It facilitates the construction of gene regulatory networks from DNA microarray data by using Bayesian network. Significant sub-modules of regulatory networks with high confidence are reconstructed by using our extended sub-network mining algorithm of directed graphs. BNArray can handle microarray datasets with missing data. To evaluate th...

Constructing Bayesian networks for criminal profiling from limited data

The increased availability of information technologies has enabled law enforcement agencies to compile databases with detailed information about major felonies. Machine learning techniques can utilize these databases to produce decision-aid tools to support police investigations. This paper presents a methodology for obtaining a Bayesian network (BN) model of offender behavior from a database o...

A Bayesian Method for Constructing Bayesian Belief Networks from Databases

This paper presents a Bayesian method for constructing Bayesian belief networks from a database of cases. Potential applications include computer-assisted hypothesis testing, automated scientific discovery, and automated construction of probabilistic expert systems. Results are presented of a preliminary evaluation of an algorithm for constructing a belief network from a database of cases. We r...