Background: Inference of gene networks typically relies on measurements across a wide range of conditions or treatments. Although one network structure is predicted, the relationship between genes could vary across conditions. A comprehensive approach to infer general and conditiondependent gene networks was evaluated. This approach integrated Bayesian network and Gaussian mixture models to describe continuous microarray gene expression measurements, and three gene networks were predicted.
Ko et al. REF integrated Bayesian network and Gaussian mixture models to describe continuous microarray gene expression measurements.
Inference of gene pathways using mixture Bayesian networks
BMC Systems Biology
BMC Systems Biology
Medicine Biology Computer Science