Biography:

In the past Yohsuke Murase has collaborated on articles with Hang-Hyun Jo. One of their most recent publications is Random walk in genome space: A key ingredient of intermittent dynamics of community assembly on evolutionary time scales. Which was published in journal Journal of Theoretical Biology.

More information about Yohsuke Murase research including statistics on their citations can be found on their Copernicus Academic profile page.

Yohsuke Murase's Articles: (3)

Random walk in genome space: A key ingredient of intermittent dynamics of community assembly on evolutionary time scales

AbstractCommunity assembly is studied using individual-based multispecies models. The models have stochastic population dynamics with mutation, migration, and extinction of species. Mutants appear as a result of mutation of the resident species, while migrants have no correlation with the resident species. It is found that the dynamics of community assembly with mutations are quite different from the case with migrations. In contrast to mutation models, which show intermittent dynamics of quasi-steady states interrupted by sudden reorganizations of the community, migration models show smooth and gradual renewal of the community. As a consequence, instead of the 1/f diversity fluctuations found for the mutation models, 1/f2, random-walk like fluctuations are observed for the migration models. In addition, a characteristic species-lifetime distribution is found: a power law that is cut off by a “skewed” distribution in the long-lifetime regime. The latter has a longer tail than a simple exponential function, which indicates an age-dependent species-mortality function. Since this characteristic profile has been observed, both in fossil data and in several other mathematical models, we conclude that it is a universal feature of macroevolution.

Stylized facts in social networks: Community-based static modeling

AbstractThe past analyses of datasets of social networks have enabled us to make empirical findings of a number of aspects of human society, which are commonly featured as stylized facts of social networks, such as broad distributions of network quantities, existence of communities, assortative mixing, and intensity-topology correlations. Since the understanding of the structure of these complex social networks is far from complete, for deeper insight into human society more comprehensive datasets and modeling of the stylized facts are needed. Although the existing dynamical and static models can generate some stylized facts, here we take an alternative approach by devising a community-based static model with heterogeneous community sizes and larger communities having smaller link density and weight. With these few assumptions we are able to generate realistic social networks that show most stylized facts for a wide range of parameters, as demonstrated numerically and analytically. Since our community-based static model is simple to implement and easily scalable, it can be used as a reference system, benchmark, or testbed for further applications.

Phase transition from poor to diverse ecosystems

AbstractA mathematical model of ecoevolution is studied. The model treats ecosystems as large dimensional dynamical systems. The preying interaction term between species have the scale invariant form of xiλxj1−λ. In addition, simple rules for addition and elimination of species are included. This model is called the “scale-invariant” model. The model makes it possible to construct ecosystems with thousands of species with a totally random invasion process, although it is not impossible when the interaction terms are the quadratic form of xixj like Lotka–Volterra equation. We studied the relation between the number of species and the interspecies interactions. As a result, it is shown the model can describe both simple ecosystems and diverse ecosystems, because this model has two phases. In one phase, the number of species remains in finite range. In the other phase, the number of species grows without limit.

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