It is well established that different sites within a protein evolve at different rates according to their role within the protein; identification of these correlated mutations can aid in tasks such as ab initio protei...It is well established that different sites within a protein evolve at different rates according to their role within the protein; identification of these correlated mutations can aid in tasks such as ab initio protein structure, structure function analysis or sequence alignment. Mutual Information is a standard measure for coevolution between two sites but its application is limited by signal to noise ratio. In this work we report a preliminary study to investigate whether larger sequence sets could circumvent this problem by calculating mutual information arrays for two sets of drug naive sequences from the HIV gpl20 protein for the B and C subtypes. Our results suggest that while the larger sequences sets can improve the signal to noise ratio, the gain is offset by the high mutation rate of the HIV virus which makes it more difficult to achieve consistent alignments. Nevertheless, we were able to predict a number of coevolving sites that were supported by previous experimental studies as well as a region close to the C terminal of the protein that was highly variable in the C subtype but highly conserved in the B subtype.展开更多
We investigate the cooperative behavior and the phase separation in a coevolving system. Agents in the system constructed by a regular random network initially play the snowdrift game with their neighbors. They try to...We investigate the cooperative behavior and the phase separation in a coevolving system. Agents in the system constructed by a regular random network initially play the snowdrift game with their neighbors. They try to obtain a better competing environment by imitating a neighbor＇s more successful strategy or cutting the connection to a defective neighbor and randomly rewiring to another agent so as to seek a better neighborhood. The dynamic process of strategy imitation and relationship among agents due to rewiring neighbors may drive the system into different states. The simulation results show that there are three different phases in the q-r plane, where q is the rewiring probability and r is the cost-to-benefit ratio. One is a static phase of a pure cooperative cluster with a few isolated defectors. The other two belong to active phases with one of a main mixed-strategy cluster and the other of a pure defective state. We find that a simple mean field theory can predict correctly the static phase and the active phase of the main mixed-strategy cluster. The theoretical boundary line between the two phases is in good agreement with the simulation result.展开更多
文摘It is well established that different sites within a protein evolve at different rates according to their role within the protein; identification of these correlated mutations can aid in tasks such as ab initio protein structure, structure function analysis or sequence alignment. Mutual Information is a standard measure for coevolution between two sites but its application is limited by signal to noise ratio. In this work we report a preliminary study to investigate whether larger sequence sets could circumvent this problem by calculating mutual information arrays for two sets of drug naive sequences from the HIV gpl20 protein for the B and C subtypes. Our results suggest that while the larger sequences sets can improve the signal to noise ratio, the gain is offset by the high mutation rate of the HIV virus which makes it more difficult to achieve consistent alignments. Nevertheless, we were able to predict a number of coevolving sites that were supported by previous experimental studies as well as a region close to the C terminal of the protein that was highly variable in the C subtype but highly conserved in the B subtype.
文摘We investigate the cooperative behavior and the phase separation in a coevolving system. Agents in the system constructed by a regular random network initially play the snowdrift game with their neighbors. They try to obtain a better competing environment by imitating a neighbor＇s more successful strategy or cutting the connection to a defective neighbor and randomly rewiring to another agent so as to seek a better neighborhood. The dynamic process of strategy imitation and relationship among agents due to rewiring neighbors may drive the system into different states. The simulation results show that there are three different phases in the q-r plane, where q is the rewiring probability and r is the cost-to-benefit ratio. One is a static phase of a pure cooperative cluster with a few isolated defectors. The other two belong to active phases with one of a main mixed-strategy cluster and the other of a pure defective state. We find that a simple mean field theory can predict correctly the static phase and the active phase of the main mixed-strategy cluster. The theoretical boundary line between the two phases is in good agreement with the simulation result.
