Proteins participating in a protein-protein interaction network can be grouped into homology classes following their common ancestry. Furthermore, homology class number and size have a high degree of universality, depending on genome size only and not on genome-specific features. These "genomic laws" can be regarded as evolutionary constraints on the growth mechanism of genomes. We define a statistical model describing the joint growth of the network and the partitioning of nodes into homology classesunder the constraint of a stochastic class-expansion/innovation model based on the "Chinese restaurant process", and we study this model through a combined mean-field and simulation approach. Additionally, we define model variants that allow to study the age dependency of interactions under different prescriptions of duplication-divergence growth. Comparing with empirical data , we show that the model reproduces the observed universal behavior allowing a variant-independent fit of parameters. This analysis also indicates that an age-dependent duplication move appears to be necessary for reproducing the basic network topological observables together with the age correlation between interacting nodes visible in empirical data  .
Proteins participating in a protein-protein interaction network can be grouped into homology classes following their common ancestry. Proteins added to the network correspond to genes added to the classes, so that the dynamics of the two objects are intrinsically linked. Here, we first introduce a statistical model describing the joint growth of the network and the partitioning of nodes into classes, which is studied through a combined mean-field and simulation approach. We then employ this unified framework to address the specific issue of the age dependence of protein interactions, through the definition of three different node wiring/divergence schemes. Comparison with empirical data indicates that an age-dependent divergence move is necessary in order to reproduce the basic topological observables together with the age correlation between interacting nodes visible in empirical data . We also discuss the possibility of nontrivial joint partition/topology observables .
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Furthermore, homology class number and size have a high degree of universality, depending on genome size only and not on genome-specific features. These "genomic laws" can be regarded as evolutionary constraints on the growth mechanism of genomes. We define
Proteins added to the network correspond to genes added to the classes, so that the dynamics of the two objects are intrinsically linked. Here, we first introduce
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homology classesunder the constraint of a stochastic class-expansion/innovation model based on the "Chinese restaurant process", and we study this model
classes, which is studied
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Additionally, we define model variants that allow to study the age dependency of interactions under different prescriptions of duplication-divergence growth. Comparing
We then employ this unified framework to address the specific issue of the age dependence of protein interactions, through the definition of three different node wiring/divergence schemes. Comparison
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, we show that the model reproduces the observed universal behavior allowing a variant-independent fit of parameters. This analysis also
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duplication move appears to be necessary for reproducing the basic network
divergence move is necessary in order to reproduce the basic
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. We also discuss the possibility of nontrivial joint partition/topology observables