Inference of genetic regulatory networks with recurrent neural network models

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Rui XuDonald C Wunsch


Large-scale gene expression data coming from microarray experiments provide us a new means to reveal fundamental cellular processes, investigate functions of genes, and understand relations and interactions among them. To infer genetic regulatory networks from these data with effective computational tools has become increasingly important Several mathematical models, including Boolean networks, Bayesian networks, dynamic Bayesian networks, and linear additive regulation models, have been used to explore the behaviors of regulatory networks. In this paper, we investigate the inference of genetic regulatory networks from time series gene expression in the framework of recurrent neural network model.

Related Concepts

Related Feeds

Brain-Computer Interface

A brain-computer interface, also known as a brain-machine interface, is a bi-directional communication pathway between an external device and a wired brain. Here is the latest research on this topic.