Networks of coupled dynamical systems have been used to model biological oscillators, Josephson junction arrays, excitable media, neural networks, spatial games, genetic control networks and many other self-organizing systems. Ordinarily, the connection topology is assumed to be either completely regular or completely random. But many biological, technological and social networks lie somewhere between these two extremes. Here we explore simple models of networks that can be tuned through this middle ground: regular networks 'rewired' to introduce increasing amounts of disorder. We find that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs. We call them 'small-world' networks, by analogy with the small-world phenomenon (popularly known as six degrees of separation. The neural network of the worm Caenorhabditis elegans, the power grid of the western United States, and the collaboration graph of film actors are shown to be small-world networks. Models of dynamical systems with small-world coupling display enhanced signal-propagation speed, computational power, and synchronizability. In particular, infectious diseases spread more easily in small-world networks than in regular lattices.

/pdf/collective-dynamics-of-small-world-networks-205zhem3gm.pdf

Collective dynamics of small-world networks

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

The emergence of order in natural systems is a constant source of inspiration for both physical and biological sciences. While the spatial order characterizing for example the crystals has been the basis of many advances in contemporary physics, most complex systems in nature do not offer such high degree of order. Many of these systems form complex networks whose nodes are the elements of the system and edges represent the interactions between them. 
Traditionally complex networks have been described by the random graph theory founded in 1959 by Paul Erdohs and Alfred Renyi. One of the defining features of random graphs is that they are statistically homogeneous, and their degree distribution (characterizing the spread in the number of edges starting from a node) is a Poisson distribution. In contrast, recent empirical studies, including the work of our group, indicate that the topology of real networks is much richer than that of random graphs. In particular, the degree distribution of real networks is a power-law, indicating a heterogeneous topology in which the majority of the nodes have a small degree, but there is a significant fraction of highly connected nodes that play an important role in the connectivity of the network. 
The scale-free topology of real networks has very important consequences on their functioning. For example, we have discovered that scale-free networks are extremely resilient to the random disruption of their nodes. On the other hand, the selective removal of the nodes with highest degree induces a rapid breakdown of the network to isolated subparts that cannot communicate with each other. 
The non-trivial scaling of the degree distribution of real networks is also an indication of their assembly and evolution. Indeed, our modeling studies have shown us that there are general principles governing the evolution of networks. Most networks start from a small seed and grow by the addition of new nodes which attach to the nodes already in the system. This process obeys preferential attachment: the new nodes are more likely to connect to nodes with already high degree. We have proposed a simple model based on these two principles wich was able to reproduce the power-law degree distribution of real networks. Perhaps even more importantly, this model paved the way to a new paradigm of network modeling, trying to capture the evolution of networks, not just their static topology.

/pdf/statistical-mechanics-of-complex-networks-1zfjpvxipu.pdf

Statistical mechanics of complex networks

Imagined communities: Reflections on the origin and spread of nationalism

https://www.thelancet.com/pdfs/journals/lancet/PIIS0140-6736(12)61766-8.pdf

A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010

https://www.arca.fiocruz.br/bitstream/icict/46002/2/Perally%2c%20Samirah%20Schistosoma%20mansoni....pdf

Schistosoma mansoni venom allergen-like protein 6 (SmVAL6) maintains tegumental barrier function.

Tactile stimulation of insoles and balance control in elderly people

Described herein are novel biological converter switches that utilize modular components, such as genetic toggle switches and single invertase memory modules (SIMMs), for converting analog inputs to digital outputs, and digital inputs to analog outputs, in cells and cellular systems. Flexibility in these biological converter switches is provided by combining individual modular components, i.e., SIMMs and genetic toggle switches, together. These biological converter switches can be combined in a variety of network topologies to create circuits that act, for example, as switchboards, and regulate the production of an output product(s) based on the combination and nature of input signals received.

Biological analog-to-digital and digital-to-analog converters

This paper discusses my own long-term research efforts to understand the interaction of schooled literacy, language diversity, and social inequality. It draws on semiotic and Marxian traditions to investigate language diversity and social inequality in contemporary European and North American settings. Focusing especially on racialization practices and class dynamics, the arguments uses early studies of minority language and schooling in order to frame a recent study of federal education policy and migrant experiences of schooling and language hierarchy.  The study draws from a year of sociolinguistic and ethnographic research among multilingual Oaxacan migrant families and communities in upstate New York, with particular focus on their children’s experience with multilingual repertoires and monolingual language polices in schooling. (Author 2012) Drawing on data from classroom lessons, district curriculum decisions, and state and federal education policies, I analyze a set of ‘state effects’ (Trouillot 2001) as they operate across different institutional sites, arguing that such effects are ways the neoliberal states attempt to regulate globalized class and racial dynamics, by shaping educational subjects who are stripped of linguistic diversity, ethnic solidarity, and class awareness. This neoliberal project, which directly contributes to the reproduction of social inequality (Menken 2008), is opposed by a variety of domestic-familial linguistic practices as well as by political movements that challenge monolingual education policy.

Literacy Practices, Linguistic Anthropology and Social Inequality

Antibiotic lethality is a complex physiological process, sensitive to external cues. Recent advances using systems approaches have revealed how events downstream of primary target inhibition actively participate in antibiotic death processes. In particular, altered metabolism, translational stress and DNA damage each contribute to antibiotic-induced cell death. Moreover, environmental factors such as oxygen availability, extracellular metabolites, population heterogeneity and multidrug contexts alter antibiotic efficacy by impacting bacterial metabolism and stress responses. Here we review recent studies on antibiotic efficacy and highlight insights gained on the involvement of cellular respiration, redox stress and altered metabolism in antibiotic lethality. We discuss the complexity found in natural environments and highlight knowledge gaps in antibiotic lethality that may be addressed using systems approaches.

James J. Collins

Papers

Schistosoma mansoni venom allergen-like protein 6 (SmVAL6) maintains tegumental barrier function.

Tactile stimulation of insoles and balance control in elderly people

Biological analog-to-digital and digital-to-analog converters

Literacy Practices, Linguistic Anthropology and Social Inequality

Antibiotic efficacy — context matters