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Carlos J. Melian

Publications and source records attributed to Carlos J. Melian.

2 recordsLinked to original sources

Unifying Theories of Molecular, Community and Network Evolution

The origin of diversification and coexistence of genes and species have been traditionally studied in isolated biological levels. Ecological and evolutionary views have focused on the mechanisms that enable or constrain species coexistence, genetic variation and the genetics of speciation, but a unified theory linking those approaches is still missing. Here we introduce evolutionary graphs in the context of neutral theories of molecular evolution and biodiversity to provide a framework that simultaneously addresses speciation rate and joint genetic and species diversities. To illuminate this question we also study two models of evolution on graphs with fitness differences, which provide insights on how genetic and ecological dynamics drive the speed of diversification. Neutral evolution generates the highest speed of speciation, species richness (i.e. five times and twice as many species as compared to genetic and ecological graphs, respectively) and genetic--species diversity (i.e., twice as many as genetic and ecological graphs, respectively). Thus the speed of speciation, the genetic--species diversity and coexistence can differ dramatically depending on whether genetic factors versus ecological factors drive the evolution of the system. By linking molecular, sexual and trophic behavior at ecological and evolutionary scales, interacting graphs can illuminate the origin and evolution of diversity and organismal coexistence.

q-bio.PE↗

Are scale-free regulatory networks larger than random ones?

Network of packages with regulatory interactions (dependences and conflicts) from Debian GNU/Linux operating system is compiled and used as analogy of a gene regulatory network. Using a trace-back algorithm we assembly networks from the potential pool of packages for both scale-free and exponential topology from real and a null model data, respectively. We calculate the maximum number of packages that can be functionally installed in the system (i.e., the active network size). We show that scale-free regulatory networks allow a larger active network size than random ones. Small genomes with scale-free regulatory topology could allow much more functionality than large genomes with an exponential one, with implications on its dynamics, robustness and evolution.

q-bio.GN↗