
Evolutionary mechanism in a self-organized system cause some functional changes that force to adapt new conformation of the interaction pattern between the components of that system. Measuring the structural differences one can retrace the evolutionary relation between two systems. We present a method to quantify the topological distance between two networks of different sizes, finding that the architectures of the networks are more similar within the same class than the outside of their class. With 43 cellular networks of different species, we show that the evolutionary relationship can be elucidated from the structural distances.
16 pages, 6 figures, 1 table
Bacteria, Statistical Mechanics (cond-mat.stat-mech), Populations and Evolution (q-bio.PE), Computational Biology, Eukaryota, FOS: Physical sciences, Quantitative Biology - Quantitative Methods, Archaea, Biological Evolution, Models, Biological, Physics - Data Analysis, Statistics and Probability, FOS: Biological sciences, Mutation, Computer Graphics, Quantitative Biology - Populations and Evolution, Condensed Matter - Statistical Mechanics, Metabolic Networks and Pathways, Phylogeny, Quantitative Methods (q-bio.QM), Data Analysis, Statistics and Probability (physics.data-an)
Bacteria, Statistical Mechanics (cond-mat.stat-mech), Populations and Evolution (q-bio.PE), Computational Biology, Eukaryota, FOS: Physical sciences, Quantitative Biology - Quantitative Methods, Archaea, Biological Evolution, Models, Biological, Physics - Data Analysis, Statistics and Probability, FOS: Biological sciences, Mutation, Computer Graphics, Quantitative Biology - Populations and Evolution, Condensed Matter - Statistical Mechanics, Metabolic Networks and Pathways, Phylogeny, Quantitative Methods (q-bio.QM), Data Analysis, Statistics and Probability (physics.data-an)
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 34 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
