We investigate the emergence of scale-free behaviour in a traffic system by using the NaSch model to simulate the evolution of traffic flow. A kind of evolution networks has been proposed, which is based on the evolut...We investigate the emergence of scale-free behaviour in a traffic system by using the NaSch model to simulate the evolution of traffic flow. A kind of evolution networks has been proposed, which is based on the evolution of the traffic flow. The network growth does not take into account preferential attachment, and the attachment of new node is independent of degree. The simulation results demonstrate that the output distribution of links is well described by a scale-free distribution.展开更多
Based on the gene-protein-reaction (GPR) model of S. cerevisiae_iND750 and the method of constraint-based analysis, we first calculated the metabolic flux distribution of S. cere-visiae_iND750. Then we calculated the ...Based on the gene-protein-reaction (GPR) model of S. cerevisiae_iND750 and the method of constraint-based analysis, we first calculated the metabolic flux distribution of S. cere-visiae_iND750. Then we calculated the deletion impact of 438 calculable genes, one by one, on the metabolic flux redistribution of S. cere-visiae_iND750. Next we analyzed the correlation between v (describing deletion impact of one gene) and d (connection degree of one gene) and the correlation between v and Vgene (flux sum controlled by one gene), and found that both of them were not of linear relation. Furthermore, we sought out 38 important genes that most greatly affected the metabolic flux distribution, and determined their functional subsystems. We also found that many of these key genes were related to many but not several subsystems. Because the in silico model of S. cere-visiae_iND750 has been tested by many ex-periments, thus is credible, we can conclude that the result we obtained has biological sig-nificance.展开更多
Constraint-based models such as flux balance analysis （FBA） are a powerful tool to study biological metabolic networks. Under the hypothesis that cells operate at an optimal growth rate as the result of evolution an...Constraint-based models such as flux balance analysis （FBA） are a powerful tool to study biological metabolic networks. Under the hypothesis that cells operate at an optimal growth rate as the result of evolution and natural selection, this model successfully predicts most cellular behaviours in growth rate. However, the model ignores the fact that cells can change their cellular metabolic states during evolution, leaving optimal metabolic states unstable. Here, we consider all the cellular processes that change metabolic states into a single term‘noise＇, and assume that cells change metabolic states by randomly walking in feasible solution space. By simulating a state of a cell randomly walking in the constrained solution space of metabolic networks, we found that in a noisy environment cells in optimal states tend to travel away from these points. On considering the competition between the noise effect and the growth effect in cell evolution, we found that there exists a trade-off between these two effects. As a result, the population of the cells contains different cellular metabolic states, and the population growth rate is at suboptimal states.展开更多
Different genes are expressed in different tissues, depending on functional objectives and selection pressures. Based on complete knowledge of the structure of the metabolic network and all the reactions taking place ...Different genes are expressed in different tissues, depending on functional objectives and selection pressures. Based on complete knowledge of the structure of the metabolic network and all the reactions taking place in the cell, elementary modes (EMs) and minimal cut sets (MCSs) can relate compounds observed in a tissue, to the genes being expressed by respectively providing the full set of non-decomposable routes of reactions and compounds that lead to the synthesis of external products, and the full set of possible target genes for blocking the synthesis of external products. So, for a particular tissue, only the EMs containing the reactions that are related to the genes being expressed in those tissues, are active for the production of the corresponding compounds. This concept is used to develop an algorithm for determining a matrix of reactions (which can be related to corresponding genes) taking place in a tissue, using experimental observations of compounds in a tissue. The program is applied to the Arabidopsis flower and identified 20 core reactions occurring in all the viable EMs. They originate from the trans-cinnamate compound and lead to the formation of kaempferol and quercetin compounds and their derivatives, as well as anthocyanin compounds. Analyses of the patterns in the matrix identify reaction sets related to certain functions such as the formation of derivatives of the two anthocyanin compounds present, as well as the reactions leading from the network’s external substrate erythrose-4P to L-Phenylalanine, cinnamyl-alc to trans-cinnamate and so on. The program can be used to successfully determine genes taking place in a tissue, and the patterns in the resulting matrix can be analysed to determine gene sets and the state of the tissue.展开更多
One approach to study the system-wide organization of biochemistry is to use statistical graph theory.In such heavily simplified methods,which disregard most of the dynamic aspects of biochemistry,one is faced with fu...One approach to study the system-wide organization of biochemistry is to use statistical graph theory.In such heavily simplified methods,which disregard most of the dynamic aspects of biochemistry,one is faced with fundamental questions.One such question is how the chemical reaction systems should be reduced to a graph retaining as much functional information as possible from the original reaction system.In these graph representations,should the edges go between substrates and products,or substrates and substrates,or both?Should vertices represent substances or reactions?Different representations encode different information about the reaction system and affect network measures in different ways.This paper investigates which representation reflects the functional organization of the metabolic system in the best way,according to the defined criteria.Four different graph representations of metabolism(three where the vertices are metabolites,one where the vertices are reactions)are evaluated using data from different organisms and databases.The graph representations are evaluated by comparing the overlap between clusters(network modules)and annotated functions,and also by comparing the set of identified currency metabolites with those that other authors have identified using qualitative biological arguments.It is found that a"substance network",where all metabolites participating in a reaction are connected,is better than others,evaluated with respect to both the functional overlap between modules and functions and to the number and identity of the identified currency metabolites.展开更多
基金Supported by the National Natural Science Foundation of China under Grant No 70471088, and the Science and Technology Foundation of Beijing Jiaotong University under Grant No 2004SM026.
文摘We investigate the emergence of scale-free behaviour in a traffic system by using the NaSch model to simulate the evolution of traffic flow. A kind of evolution networks has been proposed, which is based on the evolution of the traffic flow. The network growth does not take into account preferential attachment, and the attachment of new node is independent of degree. The simulation results demonstrate that the output distribution of links is well described by a scale-free distribution.
文摘Based on the gene-protein-reaction (GPR) model of S. cerevisiae_iND750 and the method of constraint-based analysis, we first calculated the metabolic flux distribution of S. cere-visiae_iND750. Then we calculated the deletion impact of 438 calculable genes, one by one, on the metabolic flux redistribution of S. cere-visiae_iND750. Next we analyzed the correlation between v (describing deletion impact of one gene) and d (connection degree of one gene) and the correlation between v and Vgene (flux sum controlled by one gene), and found that both of them were not of linear relation. Furthermore, we sought out 38 important genes that most greatly affected the metabolic flux distribution, and determined their functional subsystems. We also found that many of these key genes were related to many but not several subsystems. Because the in silico model of S. cere-visiae_iND750 has been tested by many ex-periments, thus is credible, we can conclude that the result we obtained has biological sig-nificance.
基金supported by the National Natural Science Foundation of China (No. 81870059,81570065)Fundamental Research Funds for the Central Universities of Central South University (No. 2018zzts039)
基金Project supported by the National Natural Science Foundation of China (Grant No 10721403)the MOST of China (Grant No2009CB918500)the National Basic Research Program of China (Grant Nos 2006CB910706 and 2007CB814800)
文摘Constraint-based models such as flux balance analysis （FBA） are a powerful tool to study biological metabolic networks. Under the hypothesis that cells operate at an optimal growth rate as the result of evolution and natural selection, this model successfully predicts most cellular behaviours in growth rate. However, the model ignores the fact that cells can change their cellular metabolic states during evolution, leaving optimal metabolic states unstable. Here, we consider all the cellular processes that change metabolic states into a single term‘noise＇, and assume that cells change metabolic states by randomly walking in feasible solution space. By simulating a state of a cell randomly walking in the constrained solution space of metabolic networks, we found that in a noisy environment cells in optimal states tend to travel away from these points. On considering the competition between the noise effect and the growth effect in cell evolution, we found that there exists a trade-off between these two effects. As a result, the population of the cells contains different cellular metabolic states, and the population growth rate is at suboptimal states.
文摘Different genes are expressed in different tissues, depending on functional objectives and selection pressures. Based on complete knowledge of the structure of the metabolic network and all the reactions taking place in the cell, elementary modes (EMs) and minimal cut sets (MCSs) can relate compounds observed in a tissue, to the genes being expressed by respectively providing the full set of non-decomposable routes of reactions and compounds that lead to the synthesis of external products, and the full set of possible target genes for blocking the synthesis of external products. So, for a particular tissue, only the EMs containing the reactions that are related to the genes being expressed in those tissues, are active for the production of the corresponding compounds. This concept is used to develop an algorithm for determining a matrix of reactions (which can be related to corresponding genes) taking place in a tissue, using experimental observations of compounds in a tissue. The program is applied to the Arabidopsis flower and identified 20 core reactions occurring in all the viable EMs. They originate from the trans-cinnamate compound and lead to the formation of kaempferol and quercetin compounds and their derivatives, as well as anthocyanin compounds. Analyses of the patterns in the matrix identify reaction sets related to certain functions such as the formation of derivatives of the two anthocyanin compounds present, as well as the reactions leading from the network’s external substrate erythrose-4P to L-Phenylalanine, cinnamyl-alc to trans-cinnamate and so on. The program can be used to successfully determine genes taking place in a tissue, and the patterns in the resulting matrix can be analysed to determine gene sets and the state of the tissue.
基金PH acknowledges support from the Swedish Foundation for Strategic Research,the Swedish Research Foundationthe Japan Society for the Promotion of Science+1 种基金the Project of Knowledge Innovation Program of Chinese Academy of Sciences via the Kavli Institute for Theoretical Physics Chinathe WCU (World Class University) program through the National Research Foundation of Korea funded by the Ministry of Education,Science and Technology(R31-2008-000-10029-0)
文摘One approach to study the system-wide organization of biochemistry is to use statistical graph theory.In such heavily simplified methods,which disregard most of the dynamic aspects of biochemistry,one is faced with fundamental questions.One such question is how the chemical reaction systems should be reduced to a graph retaining as much functional information as possible from the original reaction system.In these graph representations,should the edges go between substrates and products,or substrates and substrates,or both?Should vertices represent substances or reactions?Different representations encode different information about the reaction system and affect network measures in different ways.This paper investigates which representation reflects the functional organization of the metabolic system in the best way,according to the defined criteria.Four different graph representations of metabolism(three where the vertices are metabolites,one where the vertices are reactions)are evaluated using data from different organisms and databases.The graph representations are evaluated by comparing the overlap between clusters(network modules)and annotated functions,and also by comparing the set of identified currency metabolites with those that other authors have identified using qualitative biological arguments.It is found that a"substance network",where all metabolites participating in a reaction are connected,is better than others,evaluated with respect to both the functional overlap between modules and functions and to the number and identity of the identified currency metabolites.
