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James J. Collins

Bio: James J. Collins is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Synthetic biology & Population. The author has an hindex of 151, co-authored 669 publications receiving 89476 citations. Previous affiliations of James J. Collins include Baylor College of Medicine & University at Albany, SUNY.


Papers
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Patent
05 Mar 2003
TL;DR: In this article, the authors present methods and accompanying computer-based systems and computer-executable code stored on a computer-readable medium for constructing a model of a biological network.
Abstract: The present invention provides methods and accompanying computer-based systems and computer-executable code stored on a computer-readable medium for constructing a model of a biological network. The invention further provides methods for performing sensitivity analysis on a biological network and for identifying major regulators of species in the network and of the network as a whole. In addition, the invention provides methods for identifying targets of a perturbation such as that resulting from exposure to a compound or an environmental change. The invention further provides methods for identifying phenotypic mediators that contribute to differences in phenotypes of biological systems.

24 citations

Journal ArticleDOI
TL;DR: The significance of narrative analysis for education research is discussed by reviewing general work on the nature of narrative and examining some of the ways in which narratives vary, especially b... as discussed by the authors,...
Abstract: The significance of narrative analysis for education research is discussed by reviewing general work on the nature of narrative and examining some of the ways in which narratives vary, especially b...

24 citations

Patent
22 Dec 2009
TL;DR: In this paper, the authors proposed a single invertase memory module (SIMM) for encoding memory in cells and cellular systems, which can be easily extended to compute to high numbers, by utilizing the >100 known recombinases to create subsequent modules.
Abstract: We have created novel engineered genetic counter designs and methods of use thereof that utilize DNA recombinases to provide modular systems, termed single invertase memory modules (SIMMs), for encoding memory in cells and cellular systems. Our designs are easily extended to compute to high numbers, by utilizing the >100 known recombinases to create subsequent modules. Flexibility in our engineered genetic counter designs is provided by daisy-chaining individual modular components, i.e., SIMMs together. These modular components of the engineered genetic counters can be combined in other network topologies to create circuits that perform, amongst other things, logic and memory. Our novel engineered genetic counter designs allow for the maintenance of memory and provide the ability to count between discrete states by expressing the recombinases between their cognate recognition sites.

24 citations

Journal ArticleDOI
TL;DR: Design issues related to the planning and conduct of cohort studies of industrial low back pain (or injury)(LBP), with care given to definition and measurement of exposure and outcome events are raised.
Abstract: The connection between work-related exposures and the onset of back injury or pain is complex and not clearly understood. This paper raises design issues related to the planning and conduct of cohort studies of industrial low back pain (or injury)(LBP), with care given to definition and measurement of exposure and outcome events. These issues include sample size, outcome definition, study biases, and practical considerations when seeking and maintaining company collaboration with a research effort. Without resolving these issues, the authors conclude: (1) cohort studies of worksite-based LBP are needed to elucidate the causal associations between work tasks and LBP onset, (2) both acute and cumulative exposures should be assessed as risk factors for low back injury or pain, and (3) attention should be paid to the planning of such studies and minimization of potential biases that can limit the validity of the results. These design issues will benefit researchers and companies engaged in the planning and conduct of cohort studies of industrial LBP.

23 citations

Journal ArticleDOI
25 Mar 2005-Science
TL;DR: Two studies that combine modeling with experiments to analyze gene networks in bacteria are discussed, which enable exploration of how gene expression is regulated in bacteria.
Abstract: Gene networks can be designed that enable exploration of how gene expression is regulated, an example of synthetic biology. In their Perspective, Isaacs et al. discuss two studies ( Rosenfeld et al., Pedraza and van Oudenaarden) that combine modeling with experiments to analyze gene networks in bacteria.

23 citations


Cited by
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Journal ArticleDOI
04 Jun 1998-Nature
TL;DR: Simple models of networks that can be tuned through this middle ground: regular networks ‘rewired’ to introduce increasing amounts of disorder are explored, finding that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs.
Abstract: 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.

39,297 citations

28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组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�ly.
Abstract: 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。

18,940 citations

Journal ArticleDOI
TL;DR: In this paper, a simple model based on the power-law degree distribution of real networks was proposed, which was able to reproduce the power law degree distribution in real networks and to capture the evolution of networks, not just their static topology.
Abstract: 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.

18,415 citations

Journal ArticleDOI
TL;DR: In this paper, Imagined communities: Reflections on the origin and spread of nationalism are discussed. And the history of European ideas: Vol. 21, No. 5, pp. 721-722.

13,842 citations

Journal ArticleDOI
Stephen S Lim1, Theo Vos, Abraham D. Flaxman1, Goodarz Danaei2  +207 moreInstitutions (92)
TL;DR: In this paper, the authors estimated deaths and disability-adjusted life years (DALYs; sum of years lived with disability [YLD] and years of life lost [YLL]) attributable to the independent effects of 67 risk factors and clusters of risk factors for 21 regions in 1990 and 2010.

9,324 citations