Study On Protein Interaction And Its Network Based On Cooperative Intelligence

Membrane proteins take on a variety of functions in the life activities, and most of them play a key role in medicine design, protein functioning and immunological recognition, etc. Membrane proteins are also important medicine targets. Membrane protein interaction, especially the helical membrane protein interaction, is a considerable part in all of the protein interactions. In all kinds of tissues, almost one third of the genes are encoded to take part in membrane protein interaction. It is difficult to operate membrane proteins because of their complicated chemical properties, which make it challenging to study their interaction relationship. In this paper, we construct protein interaction network based on the combination between the attributes of complex network and bioinformatics. The study achievements provide a feasible method for the cooperative intelligence identification of membrane protein interaction, which also become new study references for potential membrane protein interaction. The detailed study contents of this paper are as follows:So many results demonstrate that protein interaction networks are not random. They have some biological regulation. In this paper, the spectrum analysis method is applied to indicate the topology structure implied in complex protein-protein interaction network, such as quasi-bipartite and quasi-clique. We calculate the degree of the separated protein network, the P value of the small network, the number of protein network nodes and so on. We also analyze the relation between these parameters, construct protein interaction network based on genetic algorithm and study it. Membrane protein interaction networks are constructed and studied based on cooperative intelligence. We compare the constructed membrane protein interaction network with general biologic network.The real protein interaction networks are sparse networks. They have so many important and dynamic properties, such as geometric effect, free scale, small world network, hierarchical structure, self similarity, affinity and specificity. We study on these important properties affecting on protein interaction networks, the static properties of protein interaction networks and the dynamic properties.At present, the membrane protein study is still in a preliminary stage, which needs more study and exploration, especially membrane protein interaction network. Based on the above study, we construct a membrane protein interaction network forecast and analysis system in this paper. We also study and explore its important attributes and dynamic characteristics, reconstruct and involve membrane protein interaction, and analyze its dynamics. Through the construction and forecasting of the membrane protein interaction network, we find out the universality rule of the membrane protein dynamics and cooperate with my lab members to validate the results. The membrane protein interaction's topology has been deduced based on its clustered index. Moreover, we study its non-scale and adaptation properties, which could provide a new method for forecasting and analysis membrane protein interaction network.Based on the constructed membrane protein interaction network, we summarize and analyze an ideal gene regulation network (GRN) model. It is defined as simple topology based on membrane protein interaction network and the dynamics on gene regulation network of the gene regulation function module input. In order to understand the dynamics of the network developing progress, integration controlling and the self properties of the membrane protein interaction network, we propose three model forms, including basic form, non-dimensionalization form and more complex form. Based on this model, membrane protein interaction nework can be simulated and its dynamic properties can be studied.The study on protein interaction is not enough now, which is far from the requirements of systematically understanding biological phenomena. Then the protein interaction data, high flux testing technology and forecasting methods have not exact standards, so it is necessary to study and explore these more deeply, such as the hub protein nodes in the protein interaction network, we also call them as medicine targets in our pharmaceutics. That will play an important part in disease and medicine now.At last, a summary of the thesis is made, and the deficiency in the project and the further development are narrated respectively.