A new gene regulatory network model based on BP algorithm for interrogating differentially expressed genes of Sea Urchin.

ABSTRACT:

Background

Computer science and mathematical theories are combined to analyze the complex interactions among genes, which are simplified to a network to establish a theoretical model for the analysis of the structure, module and dynamic properties. In contrast, traditional model of gene regulatory networks often lack an effective method for solving gene expression data because of high durational and spatial complexity. In this paper, we propose a new model for constructing gene regulatory networks using back propagation (BP) neural network based on predictive function and network topology.

Results

Combined with complex nonlinear mapping and self-learning, the BP neural network was mapped into a complex network. Network characteristics were obtained from the parameters of the

SUBMITTER: Liu L 

PROVIDER: S-EPMC5095099 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature