The Research On Algorithm Of Discovering Biological Functional Modules Based On The Regulatory Network

The systematic analysis of protein-protein interactions and regulatory effects are two of the most fundamental challenges to understand cellular organizations,processes and functions.The interaction between two proteins or regulatory effects provides significant insight into their functional association.The biological function module by the composed of macromolecule or protein have an important influence on the biological individual.These biological function modules can affect the process of very important biological significance,like the process of the production of protein,the expression of biological function,the generation of biological disease and so on.A wide range of graph theoretic computational approaches have been presented to characterize protein functions from the protein-protein interaction networks.The data mining from the biological function module in these networks has become a hot direction of bioinformatics.However,in many current researches,the research is usually based on a specific network.And ignore the inter connection between the various networks and the topological characteristics of the functional module itself.With the characteristics of network topology,there is still a great potential for the research of module mining on the network which after fusion.Fusion of the relationship between MicroRNA-genes regulatory and protein-protein interactions is a hot research in the current study.Under this background,this paper constructs the MicroRNA regulatory network by integrating MicroRNA regulatory relationship and protein-protein interaction network.And based on the topological characteristics of the bridge nodes between the network modules,an algorithm for mining biological function module on MicroRNA control network,RWRB(Random Walk with Restart and Bridge),is proposed.This algorithm is applied to the data set of human lung cancer.Get the enrichment of functional modules by gene ontology enrichment analysis,and compared with other algorithms.The comparison was found in the analysis of biological enrichment by compared with other algorithms.By observing and analyzing the relationship between the module and human disease,the enrichment of cancer gene in the module was analyzed.In the fact condition,gene is not only regulated by the MicroRNA,but also regulated by the transcription factors(TF).The relationship between transcription factor regulatory genes and DNA binding sites has been found to be more and more in recent years.In this context transcription factors have been more and more attention by researchers.In this paper,after the establishment of MicroRNA regulatory network,based on this network to continue the integration of regulatory factors to control the relationship between genes,constitute a co-regulatory network.Because there are three kinds of nodes and three kinds of edges in the co-regulation network,compared with the MicroRNA control network,it has its special characteristics.In view of this particularity,this paper improves the RWRB algorithm to constitute the RWRBC algorithm,which is suitable for the co-regulatory network.And the algorithm is applied to the human disease control network to mining the biological function module.Gene ontology enrichment analysis was carried out to obtain the biological enrichment module.The biological enrichment of these modules is stronger,and the research of lung cancer is more valuable.