Making Connections

Science (Impact Factor: 33.61). 09/2006; 313(5787):604-6. DOI: 10.1126/science.313.5787.604
Source: PubMed


Social network analysis made news as a possible tool for scanning phone records for security threats, but the field is exerting
a broader impact in business, biology, computer networks--and movie titles. (Read more.)

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    • "Here, the most descriptive factor was θ1, which includes the clustering coefficients. The interpretation of the clustering coefficient used in this study is also often used in sociology and biochemical networks (see, for example, [15,17]). There are other interpretations of the clustering coefficient, such as that described by Soffer et al. [18]. "
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    ABSTRACT: Background: The set of extreme pathways (ExPa), {pi}, defines the convex basis vectors used for the mathematical characterization of the null space of the stoichiometric matrix for biochemical reaction networks. ExPa analysis has been used for a number of studies to determine properties of metabolic networks as well as to obtain insight into their physiological and functional states in silico. However, the number of ExPas, p = {pi} , grows with the size and complexity of the network being studied, and this poses a computational challenge. For this study, we investigated the relationship between the number of extreme pathways and simple network properties. Results: We established an estimating function for the number of ExPas using these easily obtainable network measurements. In particular, it was found that log [p] had an exponential relationship with log [∑i=1Rd1d+1 c1], where R = Reff is the number of active reactions in a network, d-i and d+i the incoming and outgoing degrees of the reactions ri ∈ Reff, and ci the clustering coefficient for each active reaction. Conclusion: This relationship typically gave an estimate of the number of extreme pathways to within a factor of 10 of the true number. Such a function providing an estimate for the total number of ExPas for a given system will enable researchers to decide whether ExPas analysis is an appropriate investigative tool.
    BMC Bioinformatics 02/2007; 8(1):363. DOI:10.1186/1471-2105-8-363 · 2.58 Impact Factor
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    ABSTRACT: If handled appropriately, data about Internet-based communication and interactivity could revolutionize our understanding of collective human behaviour.
    Nature 03/2007; 445(7127):489. DOI:10.1038/445489a · 41.46 Impact Factor
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    ABSTRACT: In this article, we support the case that the neurotoxic agent in Alzheimer's disease is a soluble aggregated form of the amyloid beta peptide (Abeta), probably complexed with divalent copper. The structure and chemical properties of the monomeric peptide and its Cu(ii) complex are discussed, as well as what little is known about the oligomeric species. Abeta oligomers are neurotoxic by a variety of mechanisms. They adhere to plasma and intracellular membranes and cause lesions by a combination of radical-initiated lipid peroxidation and formation of ion-permeable pores. In endothelial cells this damage leads to loss of integrity of the blood-brain barrier and loss of blood flow to the brain. At synapses, the oligomers close neuronal insulin receptors, mirroring the effects of Type II diabetes. In intracellular membranes, the most damaging effect is loss of calcium homeostasis. The oligomers also bind to a variety of substances, mostly with deleterious effects. Binding to cholesterol is accompanied by its oxidation to products that are themselves neurotoxic. Possibly most damaging is the binding to tau, and to several kinases, that results in the hyperphosphorylation of the tau and abrogation of its microtubule-supporting role in maintaining axon structure, leading to diseased synapses and ultimately the death of neurons. Several strategies are presented and discussed for the development of compounds that prevent the oligomerization of Abeta into the neurotoxic species.
    Dalton Transactions 04/2008; 14(10):1273-82. DOI:10.1039/b718601k · 4.20 Impact Factor
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