Investigation Of Two Related Problems On Complex Systems

With the rapid development of science and technology and the rapid expansionof human knowledge, complex systems, countered and to deal with by people, are in-creasingly complicated. For example, the structure of the spacecraft, large-scale sensornetworks, information transmission and reception process of the large-scale networks,life sciences, ecological systems reproduce the evolution and biological engineering.These complex characteristics of complex systems are nonlinear, stochastic, infinite di-mensional, strongly coupled, multi-level and uncertainty and so on. Complex systemsand complexity science considered to be the forefront of scientific development in the21st century, have become a common research focus of physics, engineering, biologyand other disciplines. To study and understanding of complex systems, enables people tolook at from a holistic point of view and understand complex things,thus,makes peoplefurther to implement, control and use them.In the past few years, with the rapid development of communication networks,internet, large-scale sensor networks, transportation networks and other applications, in-formation network has become a subject as the research of complex systems. In addi-tion, the issue of biological networks is not only an objective basis of the development ofcomplex network theory, but also one of the core end-result of complex network theory.The study of biological networks is developing rapidly, research methods, and forms aremany and varied. Among them, the gene regulatory networks is a universal concern.In this paper, two complex systems are investigated, namely, information networks, andbiological regulatory networks.For information network, the investigation in this paper is the positioning of wire-less sensor networks. Here, we give a new range-free positioning algorithm based Agentmodeling, called the Spring swarm localization algorithm (SSLA). The SSLA makesthe transmission of information as well as the complex interactions between adjacentnodes in the network, and makes each node oscillate around its relative equilibrium po-sition, and during positioning a WSN makes the movement of node in the entire networkwith a control, so that makes the oscillation amplitude of each node reduce, and ulti-mately makes the entire network get the positioning information in the complex systemsemerged way. We point out that the positioning algorithm has a high positioning accu-racy and the positioning accuracy can reach10%or more, the localization algorithm canbe applied to the lower anchor node density sensor networks. At the same time, the po-sitioning algorithm does not depend on network distribution. The localization algorithmis simple, efcient and can be applied to positioning large-scale WSNs.Two aspects dynamics of biological regulatory networks are investigated in thiswork,ie, the bistable switches and robustness of embryonic stem cell regulatory networkand the use of the Boolean network method to study the p53gene regulatory network.As for the bistable switch and the robustness of regulatory networks of embryonic stem cell,a mathematical model was established for REST and miR-21and transcriptionfactors OCT4, SOX2and NANOG, and the results will explained for the results of therelevant literature. Further concussion is draw that to change the decay rate coefcientof REST or the generate rate coefcient miR-21will cause the translation of the bistablecurve, and afect the length of the switch. It is more significant that to change the decayrate coefcient the REST compared to the generation rate coefcient change of miR-21. Evolutionary processes in biological systems, robustness is the basic nature, wehypothesized that the biological system has the ability to evolve to the direction of themost robust. To further understand the biological robustness will help people furtherto understand and speculate the structure and function of the biochemical regulatorynetworks. We investigated the embryonic the stem cell core regulatory network withcomprehensive efect two external input signals A and B of the bistable a switch, andresults show that a more robust bistable switch will be got by the appropriate integratetwo external input signals. Furthermore, we also speculated about the two external inputsignals A and B that the signal A plays a major role in the maintenance of normal EScells self-renewal and diferentiation, and the signal B plays an important role in themaintenance the robustness of embryonic stem cell regulatory network.p53gene regulatory network plays an important role in many cellular processessuch as aging, metabolism, autophagy, angiogenesis and DNA repair. These processesare involved in tumor formation, while, p53has the function of tumor suppressor. Under-standing of p53gene regulatory network and then applied to the clinical will bring hopethe treatment of related diseases. However, it is still a creative field that efectively p53research transition to clinical. Here, we use the Boolean network approach to investigatep53gene regulatory network. Firstly, we present the concept of compression code aboutboolean matrix, and use the compression code to calculate attractors of boolean network.Secondly, we propose the approach based on biochemical reactions to analysis specificgene regulatory networks. Then, from the various relevant literature, we summarize andestablish the p53gene regulatory network model, and take advantage of the proposedthe approach to analysis the p53gene regulatory networks. We obtain the results whichwell explain some experimental phenomena in the p53gene regulatory network. At thesame time, the work predicts there is a positive feedback loop in the p53core regulatorynetwork consist of p53Pâ†'XXXPâ†'p53P. Due to the importance of the p53generegulatory network, any further understanding of the network may be related to treatmentof disease, especially cancer treatment with new breakthroughs. Of course, the results inthis paper should further be confirmed in biological experiments.