According to the Statistical Communiqué of the People's Republic of China on the 2008 National Economic and Social Development,released by the National Bureau of Statistics of China on Feb.26,in 2008,the nati...According to the Statistical Communiqué of the People's Republic of China on the 2008 National Economic and Social Development,released by the National Bureau of Statistics of China on Feb.26,in 2008,the national economy kept fast growth and all social undertakings achieved new progress.展开更多
Since the beginning of 2012,the international political and economic environment becomes more complex and volatile,so China’s economic development faces increasing difficulties.China’s economic growth has slowed dow...Since the beginning of 2012,the international political and economic environment becomes more complex and volatile,so China’s economic development faces increasing difficulties.China’s economic growth has slowed down,with GDP growth rate of 8.1%,7.6%,and 7.4%for the first,second and third quarter respectively.What China’s current economic situation is and how the future development trend will be展开更多
A decade ago mainstream molecular biologists regarded it impossible or biologically ill-motivated to understand the dynamics of complex biological phenomena, such as cancer genesis and progression, from a network pers...A decade ago mainstream molecular biologists regarded it impossible or biologically ill-motivated to understand the dynamics of complex biological phenomena, such as cancer genesis and progression, from a network perspective. Indeed, there are numerical difficulties even for those who were determined to explore along this direction. Undeterred, seven years ago a group of Chinese scientists started a program aiming to obtain quantitative connections between tumors and network dynamics. Many interesting results have been obtained. In this paper we wish to test such idea from a different angle: the connection between a normal biological process and the network dynamics. We have taken early myelopoiesis as our biological model. A standard roadmap for the cell-fate diversification during hematopoiesis has already been well established experimentally, yet little was known for its underpinning dynamical mechanisms. Compounding this difficulty there were additional experimental challenges, such as the seemingly conflicting hematopoietic roadmaps and the cell-fate inter-conversion events. With early myeloid cell-fate determination in mind, we constructed a core molecular endogenous network from well-documented gene regulation and signal transduction knowledge. Turning the network into a set of dynamical equations, we found computationally several structurally robust states. Those states nicely correspond to known cell phenotypes. We also found the states connecting those stable states.They reveal the developmental routes—how one stable state would most likely turn into another stable state. Such interconnected network among stable states enabled a natural organization of cell-fates into a multi-stable state landscape. Accordingly, both the myeloid cell phenotypes and the standard roadmap were explained mechanistically in a straightforward manner. Furthermore,recent challenging observations were also explained naturally. Moreover, the landscape visually enables a prediction of a pool of additional cell states and developmental routes, including the non-sequential and cross-branch transitions, which are testable by future experiments. In summary, the endogenous network dynamics provide an integrated quantitative framework to understand the heterogeneity and lineage commitment in myeloid progenitors.展开更多
文摘According to the Statistical Communiqué of the People's Republic of China on the 2008 National Economic and Social Development,released by the National Bureau of Statistics of China on Feb.26,in 2008,the national economy kept fast growth and all social undertakings achieved new progress.
文摘Since the beginning of 2012,the international political and economic environment becomes more complex and volatile,so China’s economic development faces increasing difficulties.China’s economic growth has slowed down,with GDP growth rate of 8.1%,7.6%,and 7.4%for the first,second and third quarter respectively.What China’s current economic situation is and how the future development trend will be
基金supported by the National Basic Research Program of China(2010CB529200)National Natural Science Foundation of China(91029738)
文摘A decade ago mainstream molecular biologists regarded it impossible or biologically ill-motivated to understand the dynamics of complex biological phenomena, such as cancer genesis and progression, from a network perspective. Indeed, there are numerical difficulties even for those who were determined to explore along this direction. Undeterred, seven years ago a group of Chinese scientists started a program aiming to obtain quantitative connections between tumors and network dynamics. Many interesting results have been obtained. In this paper we wish to test such idea from a different angle: the connection between a normal biological process and the network dynamics. We have taken early myelopoiesis as our biological model. A standard roadmap for the cell-fate diversification during hematopoiesis has already been well established experimentally, yet little was known for its underpinning dynamical mechanisms. Compounding this difficulty there were additional experimental challenges, such as the seemingly conflicting hematopoietic roadmaps and the cell-fate inter-conversion events. With early myeloid cell-fate determination in mind, we constructed a core molecular endogenous network from well-documented gene regulation and signal transduction knowledge. Turning the network into a set of dynamical equations, we found computationally several structurally robust states. Those states nicely correspond to known cell phenotypes. We also found the states connecting those stable states.They reveal the developmental routes—how one stable state would most likely turn into another stable state. Such interconnected network among stable states enabled a natural organization of cell-fates into a multi-stable state landscape. Accordingly, both the myeloid cell phenotypes and the standard roadmap were explained mechanistically in a straightforward manner. Furthermore,recent challenging observations were also explained naturally. Moreover, the landscape visually enables a prediction of a pool of additional cell states and developmental routes, including the non-sequential and cross-branch transitions, which are testable by future experiments. In summary, the endogenous network dynamics provide an integrated quantitative framework to understand the heterogeneity and lineage commitment in myeloid progenitors.
