抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.

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The Structure and Function of Complex Networks

Certain subsystems of nonlinear, chaotic systems can be made to synchronize by linking them with common signals. The criterion for this is the sign of the sub-Lyapunov exponents. We apply these ideas to a real set of synchronizing chaotic circuits.

Synchronization in chaotic systems

The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of graphs representing real systems is community structure, or clustering, i. e. the organization of vertices in clusters, with many edges joining vertices of the same cluster and comparatively few edges joining vertices of different clusters. Such clusters, or communities, can be considered as fairly independent compartments of a graph, playing a similar role like, e. g., the tissues or the organs in the human body. Detecting communities is of great importance in sociology, biology and computer science, disciplines where systems are often represented as graphs. This problem is very hard and not yet satisfactorily solved, despite the huge effort of a large interdisciplinary community of scientists working on it over the past few years. We will attempt a thorough exposition of the topic, from the definition of the main elements of the problem, to the presentation of most methods developed, with a special focus on techniques designed by statistical physicists, from the discussion of crucial issues like the significance of clustering and how methods should be tested and compared against each other, to the description of applications to real networks.

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Community detection in graphs

We prove the existence of front solutions for the Ginzburg-Landau equation

$$\partial _t u(x,t) = \partial _x^2 u(x,t) + (1 - |u(x,t)|^2 )u(x,t)$$

, interpolating between two stationary solutions of the form$u(x) = \sqrt {1 - q^2 } e^{iqx}$ with different values ofq atx=±∞. Such fronts are shown to exist when at least one of theq is in the Eckhaus-unstable domain.

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Front solutions for the Ginzburg-Landau equation

Non-equilibrium steady states for chains of oscillators (masses) connected by harmonic and anharmonic springs and interacting with heat baths at different temperatures have been the subject of several studies. In this paper, we show how some of the results extend to more complicated networks. We establish the existence and uniqueness of the non-equilibrium steady state, and show that the system converges to it at an exponential rate. The arguments are based on controllability and conditions on the potentials at infinity.

Non-Equilibrium Steady States for Networks of Oscillators.

We begin a study of normal form theorems for parabolic partial differential equations. We show that despite the presence of resonances one can construct a partial normal form for perturbations of the Ginzburg-Landau equation. The normal form transformation is expressed in terms of singular integral operators, whose behavior can be controlled in the appropriate function spaces

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Normal forms for parabolic partial differential equations

In an earlier paper, we proved the validity of large deviations theory for the particle approximation of quite general chemical reaction networks. In this paper, we extend its scope and present a more geometric insight into the mechanism of that proof, exploiting the notion of spherical image of the reaction polytope. This allows to view the asymptotic behavior of the vector field describing the mass-action dynamics of chemical reactions as the result of an interaction between the faces of this polytope in different dimensions. We also illustrate some local aspects of the problem in a discussion of Wentzell–Freidlin theory, together with some examples.

On the Geometry of Chemical Reaction Networks: Lyapunov Function and Large Deviations

We consider the Taylor-Couette problem in an infinitely extended cylindrical domain. There exist modulated front solutions which describe the spreading of the stable Taylor vortices into the region of the unstable Couette flow. These transient solutions have the form of a front-like envelope advancing in the laboratory frame and leaving behind the stationary, spatially periodic Taylor vortices. We prove the nonlinear stability of these solutions with respect to small spatially localized perturbations.

Jean-Pierre Eckmann

Papers

Front solutions for the Ginzburg-Landau equation

Non-Equilibrium Steady States for Networks of Oscillators.

Normal forms for parabolic partial differential equations

On the Geometry of Chemical Reaction Networks: Lyapunov Function and Large Deviations

Nonlinear Stability of Bifurcating Front Solutions for the Taylor-Couette Problem