Prediction of microbial communities for urban metagenomics using neural network approach.

BACKGROUND:Microbes are greatly associated with human health and disease, especially in densely populated cities. It is essential to understand the microbial ecosystem in an urban environment for cities to monitor the transmission of infectious diseases and detect potentially urgent threats. To achieve this goal, the DNA sample collection and analysis have been conducted at subway stations in major cities. However, city-scale sampling with the fine-grained geo-spatial resolution is expensive and laborious. In this paper, we introduce MetaMLAnn, a neural network based approach to infer microbial communities at unsampled locations given information reflecting different factors, including subway line networks, sampling material types, and microbial composition patterns. RESULTS:We evaluate the effectiveness of MetaMLAnn based on the public metagenomics dataset collected from multiple locations in the New York and Boston subway systems. The experimental results suggest that MetaMLAnn consistently performs better than other five conventional classifiers under different taxonomic ranks. At genus level, MetaMLAnn can achieve F1 scores of 0.63 and 0.72 on the New York and the Boston datasets, respectively. CONCLUSIONS:By exploiting heterogeneous features, MetaMLAnn captures the hidden interactions between microbial compositions and the urban environment, which enables precise predictions of microbial communities at unmeasured locations

Quantum Chaos, Irreversible Classical Dynamics and Random Matrix Theory

The Bohigas--Giannoni--Schmit conjecture stating that the statistical spectral properties of systems which are chaotic in their classical limit coincide with random matrix theory is proved. For this purpose a new semiclassical field theory for individual chaotic systems is constructed in the framework of the non--linear $\sigma$-model. The low lying modes are shown to be associated with the Perron--Frobenius spectrum of the underlying irreversible classical dynamics. It is shown that the existence of a gap in the Perron-Frobenius spectrum results in a RMT behavior. Moreover, our formalism offers a way of calculating system specific corrections beyond RMT.Comment: 4 pages, revtex, no figure

Classical and Quantum Dynamics in a Random Magnetic Field

Using the supersymmetry approach, we study spectral statistical properties of a two-dimensional quantum particle subject to a non-uniform magnetic field. We focus mainly on the problem of regularisation of the field theory. Our analysis begins with an investigation of the spectral properties of the purely classical evolution operator. We show that, although the kinetic equation is formally time-reversible, density relaxation is controlled by {\em irreversible} classical dynamics. In the case of a weak magnetic field, the effective kinetic operator corresponds to diffusion in the angle space, the diffusion constant being determined by the spectral resolution of the inhomogeneous magnetic field. Applying these results to the quantum problem, we demonstrate that the low-lying modes of the field theory are related to the eigenmodes of the irreversible classical dynamics, and the higher modes are separated from the zero mode by a gap associated with the lowest density relaxation rate. As a consequence, we find that the long-time properties of the system are characterised by universal Wigner-Dyson statistics. For a weak magnetic field, we obtain a description in terms of the quasi one-dimensional non-linear $\sigma$-model.Comment: 16 pages, RevTe