Reconstruction of Gene Regulatory Network based on Dynamic Bayesian Network


  • Gong Jiao


—With the rapid development of biotechnology and experimental conditions, people can obtain
high-throughput gene expression data in a short time, which lays a foundation for studying and revealing the
relationship between genes and their products, especially the regulation mechanism of gene expression.
According to geometric patterns, the potential regulators and regulatory delays are determined, and the
regulatory relationships among genes are discovered by reasoning the correlation between these geometric
patterns. This method solves the problem of mining trend-related gene regulatory relationships, simplifies
the problem of network construction in scale, shortens the learning time and makes the network structure
more stable. It can estimate and predict the state of observed values at multiple times, and can show the
interaction of gene regulation process. It provides an effective tool for revealing gene regulatory network