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Reiko Tanaka

Publications and source records attributed to Reiko Tanaka.

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Towards a Theory of Scale-Free Graphs: Definition, Properties, and Implications (Extended Version)

Although the ``scale-free'' literature is large and growing, it gives neither a precise definition of scale-free graphs nor rigorous proofs of many of their claimed properties. In fact, it is easily shown that the existing theory has many inherent contradictions and verifiably false claims. In this paper, we propose a new, mathematically precise, and structural definition of the extent to which a graph is scale-free, and prove a series of results that recover many of the claimed properties while suggesting the potential for a rich and interesting theory. With this definition, scale-free (or its opposite, scale-rich) is closely related to other structural graph properties such as various notions of self-similarity (or respectively, self-dissimilarity). Scale-free graphs are also shown to be the likely outcome of random construction processes, consistent with the heuristic definitions implicit in existing random graph approaches. Our approach clarifies much of the confusion surrounding the sensational qualitative claims in the scale-free literature, and offers rigorous and quantitative alternatives.

cond-mat.dis-nn

Some protein interaction data do not exhibit power law statistics

It has been claimed that protein-protein interaction (PPI) networks are scale-free based on the observation that the node degree sequence follows a power law. Here we argue that these claims are likely to be based on erroneous statistical analysis. Typically, the supporting data are presented using frequency-degree plots. We show that such plots can be misleading, and should correctly be replaced by rank-degree plots. We provide two PPI network examples in which the frequency-degree plots appear linear on a log-log scale, but the rank-degree plots demonstrate that the node degree sequence is far from a power law. We conclude that at least these PPI networks are not scale-free.

q-bio.MN

Scale-rich metabolic networks: background and introduction

Recent progress has clarified many features of the global architecture of biological metabolic networks, which have highly organized and optimized tolerances and tradeoffs (HOT) for functional requirements of flexibility, efficiency, robustness, and evolvability, with constraints on conservation of energy, redox, and many small moieties. One consequence of this architecture is a highly structured modularity that is self-dissimilar and scale-rich, with extremes in low and high variability, including power laws, in both metabolite and reaction degree distributions. This paper illustrates these features using the well-understood stoichiometry of metabolic networks in bacteria, and a simple model of an abstract metabolism.

q-bio.MN