137 research outputs found

    Signatures of arithmetic simplicity in metabolic network architecture

    Get PDF
    Metabolic networks perform some of the most fundamental functions in living cells, including energy transduction and building block biosynthesis. While these are the best characterized networks in living systems, understanding their evolutionary history and complex wiring constitutes one of the most fascinating open questions in biology, intimately related to the enigma of life's origin itself. Is the evolution of metabolism subject to general principles, beyond the unpredictable accumulation of multiple historical accidents? Here we search for such principles by applying to an artificial chemical universe some of the methodologies developed for the study of genome scale models of cellular metabolism. In particular, we use metabolic flux constraint-based models to exhaustively search for artificial chemistry pathways that can optimally perform an array of elementary metabolic functions. Despite the simplicity of the model employed, we find that the ensuing pathways display a surprisingly rich set of properties, including the existence of autocatalytic cycles and hierarchical modules, the appearance of universally preferable metabolites and reactions, and a logarithmic trend of pathway length as a function of input/output molecule size. Some of these properties can be derived analytically, borrowing methods previously used in cryptography. In addition, by mapping biochemical networks onto a simplified carbon atom reaction backbone, we find that several of the properties predicted by the artificial chemistry model hold for real metabolic networks. These findings suggest that optimality principles and arithmetic simplicity might lie beneath some aspects of biochemical complexity

    "Open Innovation" and "Triple Helix" Models of Innovation: Can Synergy in Innovation Systems Be Measured?

    Get PDF
    The model of "Open Innovations" (OI) can be compared with the "Triple Helix of University-Industry-Government Relations" (TH) as attempts to find surplus value in bringing industrial innovation closer to public R&D. Whereas the firm is central in the model of OI, the TH adds multi-centeredness: in addition to firms, universities and (e.g., regional) governments can take leading roles in innovation eco-systems. In addition to the (transversal) technology transfer at each moment of time, one can focus on the dynamics in the feedback loops. Under specifiable conditions, feedback loops can be turned into feedforward ones that drive innovation eco-systems towards self-organization and the auto-catalytic generation of new options. The generation of options can be more important than historical realizations ("best practices") for the longer-term viability of knowledge-based innovation systems. A system without sufficient options, for example, is locked-in. The generation of redundancy -- the Triple Helix indicator -- can be used as a measure of unrealized but technologically feasible options given a historical configuration. Different coordination mechanisms (markets, policies, knowledge) provide different perspectives on the same information and thus generate redundancy. Increased redundancy not only stimulates innovation in an eco-system by reducing the prevailing uncertainty; it also enhances the synergy in and innovativeness of an innovation system.Comment: Journal of Open Innovations: Technology, Market and Complexity, 2(1) (2016) 1-12; doi:10.1186/s40852-016-0039-

    Stable Isotopic Evidence for Methane Seeps in Neoproterozoic Postglacial Cap Carbonates

    Get PDF
    The Earth's most severe glaciations are thought to have occurred about 600 million years ago, in the late Neoproterozoic era. A puzzling feature of glacial deposits from this interval is that they are overlain by 1–5-m-thick 'cap carbonates' (particulate deep-water marine carbonate rocks) associated with a prominent negative carbon isotope excursion. Cap carbonates have been controversially ascribed to the aftermath of almost complete shutdown of the ocean ecosystems for millions of years during such ice ages—the 'snowball Earth' hypothesis. Conversely, it has also been suggested that these carbonate rocks were the result of destabilization of methane hydrates during deglaciation and concomitant flooding of continental shelves and interior basins. The most compelling criticism of the latter 'methane hydrate' hypothesis has been the apparent lack of extreme isotopic variation in cap carbonates inferred locally to be associated with methane seeps. Here we report carbon isotopic and petrographic data from a Neoproterozoic postglacial cap carbonate in south China that provide direct evidence for methane-influenced processes during deglaciation. This evidence lends strong support to the hypothesis that methane hydrate destabilization contributed to the enigmatic cap carbonate deposition and strongly negative carbon isotopic anomalies following Neoproterozoic ice ages. This explanation requires less extreme environmental disturbance than that implied by the snowball Earth hypothesis

    Non Linear Programming (NLP) Formulation for Quantitative Modeling of Protein Signal Transduction Pathways

    Get PDF
    Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.National Institutes of Health (U.S.) (Grant P50-GM068762)National Institutes of Health (U.S.) (Grant R24-DK090963)United States. Army Research Office (Grant W911NF-09-0001)German Research Foundation (Grant GSC 111

    Toward a Chronology Standard for Project CRER

    No full text
    corecore