http://precedings.nature.com/tags/network Recently posted documents tagged with 'network' Nature Publishing Group en Nature Precedings http://precedings.nature.com/images/header_logo.gif http://precedings.nature.com http://dx.doi.org/10.1038/npre.2009.3724.1 Standard graphical representations have played a crucial role in science and engineering throughout the last century. Without electrical symbolism, it is very likely that our industrial society would not have evolved at the same pace. Similarly, specialized notations such as the Feynmann notation or the process flow diagrams did a lot for the adoption of concepts in their own fields. With the advent of Systems Biology, and more recently of Synthetic Biology, the need for precise and unambiguous descriptions of biochemical interactions has become more pressing. While some ideas have been advanced over the last decade, with a few detailed proposals, no actual community standard has emerged. The Systems Biology Graphical Notation (SBGN) is a graphical representation crafted over several years by a community of biochemists, modellers and computer scientists. Three orthogonal and complementary languages have been created, the Process Descriptions, the Entity Relationships and the Activity Flows. Using these three idioms a scientist can represent any network of biochemical interactions, which can then be interpreted in an unambiguous way. The set of symbols used is limited, and the grammar quite simple, to allow its usage ranging from textbooks and teaching in high schools to peer reviewed articles in scientific journals. The first level of the SBGN Activity Flow language has been publicly released. Shared by the communities of biochemists, genomic scientists, theoreticians and computational biologists, SBGN languages will foster efficient storage, exchange and reuse of information on signaling pathways, metabolic networks and gene regulatory maps. http://dx.doi.org/10.1038/npre.2009.3724.1 Mon, 07 Sep 2009 19:43:48 UTC Systems Biology Graphical Notation: Activity Flow language Level 1 doi:10.1038/npre.2009.3724.1 2009-09-07 Huaiyu Mi Nature Precedings 2009-09-07T19:43:48Z Manuscript Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3719.1 Standard graphical representations have played a crucial role in science and engineering throughout the last century. Without electrical symbolism, it is very likely that our industrial society would not have evolved at the same pace. Similarly, specialised notations such as the Feynmann notation or the process flow diagrams did a lot for the adoption of concepts in their own fields. With the advent of Systems Biology, and more recently of Synthetic Biology, the need for precise and unambiguous descriptions of biochemical interactions has become more pressing. While some ideas have been advanced over the last decade, with a few detailed proposals, no actual community standard has emerged. The Systems Biology Graphical Notation (SBGN) is a graphical representation crafted over several years by a community of biochemists, modellers and computer scientists. Three orthogonal and complementary languages have been created, the Process Descriptions, the Entity Relationships and the Activity Flows. Using these three idioms a scientist can represent any network of biochemical interactions, which can then be interpreted in an unambiguous way. The set of symbols used is limited, and the grammar quite simple, to allow its usage in textbooks and its teaching directly in high schools. The first level of the SBGN Entity Relationship language has been publicly released. Shared by the communities of biochemists, genomicians, theoreticians and computational biologists, SBGN languages will foster efficient storage, exchange and reuse of information on signalling pathways, metabolic networks and gene regulatory maps. http://dx.doi.org/10.1038/npre.2009.3719.1 Fri, 04 Sep 2009 15:21:22 UTC Systems Biology Graphical Notation: Entity Relationship language Level 1 doi:10.1038/npre.2009.3719.1 2009-09-04 Nicolas Le Novère Nature Precedings 2009-09-04T15:21:22Z Manuscript Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://precedings.nature.com/documents/2893/version/1 Large-scale recording from populations of neurons is a promising strategy in the study of complex brain function. Here we introduce a simple optical technique that simultaneously probes the calcium activity of ~10,000 cells at the single cell resolution in vitro. We employed a combination of a low-magnification objective lens and an electron-multiplying charge-coupled device megapixel camera to achieve large-view-field and high-resolution imaging. http://precedings.nature.com/documents/2893/version/1 Mon, 23 Feb 2009 20:00:05 UTC Large-scale imaging of brain network activity from >10,000 neocortical cells hdl:10101/npre.2009.2893.1 2009-02-23 Yuji Ikegaya Nature Precedings 2009-02-23T20:00:05Z Manuscript Neuroscience Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://precedings.nature.com/documents/2610/version/1 The analysis of network topology and dynamics is increasingly used for the description of the structure, function and evolution of complex systems. Here we summarize key aspects of the evolvability and robustness of the hierarchical network-set of macromolecules, cells, organisms, and ecosystems. Listing the costs and benefits of cooperation as a necessary behaviour to build this network hierarchy, we outline the major hypothesis of the paper: the emergence of hierarchical complexity needs cooperation leading to the ageing of the constituent networks. Local cooperation in a stable environment may lead to over-optimization developing an ‘always-old’ network, which ages slowly, and dies in an apoptosis-like process. Global cooperation by exploring a rapidly changing environment may cause an occasional over-perturbation exhausting system-resources, causing rapid degradation, ageing and death of an otherwise ‘forever-young’ network in a necrosis-like process. Giving a number of examples we explain how local and global cooperation can both evoke and help successful ageing. Finally, we show how various forms of cooperation and consequent ageing emerge as key elements in all major steps of evolution from the formation of protocells to the establishment of the globalized, modern human society. Thus, ageing emerges as a price of complexity, which is going hand-in-hand with cooperation enhancing each other in a successful community. http://precedings.nature.com/documents/2610/version/1 Fri, 05 Dec 2008 21:01:30 UTC Ageing as a price of cooperation and complexity: Self-organization of complex systems causes the ageing of constituent networks hdl:10101/npre.2008.2610.1 2008-12-05 Peter Csermely Nature Precedings 2008-12-05T21:01:30Z Manuscript Genetics & Genomics Bioinformatics Evolutionary Biology http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2008.2562.1 An expanding body of literature describes the existence of concerted brain activations in the absence of any external stimuli. Resting-state networks have been identified and demonstrated to be modulated during the performance of specific cognitive operations. However, despite mounting evidence the possibility still remains that those correlated signal fluctuations reflect non-neural phenomena. In order to isolate functionally relevant spontaneous coactivations, we utilized a multi-level sampling approach to obtain co-registered brain signals across a range of sampling resolution and sensitivity. Surface and local field potentials, hemodynamic signals (near-infrared spectroscopy, NIRS), and cell spiking were recorded from dorsolateral prefrontal and posterior parietal cortices in four monkeys trained to remain motionless in a primate chair. The use of an optical recording technique (NIRS) allows measurement of a signal that is physiologically equivalent to that obtained using BOLD fMRI, though with millisecond temporal resolution and minimal technical or environmental constraints. The different signal types exhibited correlations between the two regions of interest in both the frequency and time domains. This evidence suggests that the resting-state network activations detected by fMRI do in fact reflect functional coactivations of areas across multiple levels of network communication. http://dx.doi.org/10.1038/npre.2008.2562.1 Tue, 25 Nov 2008 16:49:48 UTC Hemodynamic and electrophysiological evidence of resting-state network activity in the primate doi:10.1038/npre.2008.2562.1 2008-11-25 Allen Ardestani Nature Precedings 2008-11-25T16:49:48Z Poster Neuroscience http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2008.2265.1 Information on protein-protein and protein-chemical interactions is essential for understanding cellular functions. The STRING and STITCH web resources integrate interaction evidence derived from pathways, automatic literature mining, primary experimental data, and genomic context. The resulting interaction networks cover 1.5 million proteins from 373 organisms and 68,000 chemicals. http://dx.doi.org/10.1038/npre.2008.2265.1 Mon, 08 Sep 2008 15:35:28 UTC STRING and STITCH: known and predicted interactions between proteins and chemicals doi:10.1038/npre.2008.2265.1 2008-09-08 Lars J. Jensen Nature Precedings 2008-09-08T15:35:28Z Poster Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://precedings.nature.com/documents/35/version/2 In recent years, in-silico literature-based mammalian protein-protein interaction network datasets have been developed. These datasets contain binary interactions extracted manually from legacy experimental biomedical research literature. Placing lists of genes or proteins identified as significantly changing in multivariate experiments, in the context of background knowledge about binary interactions, can be used to place these genes or proteins in the context of pathways and protein complexes.Genes2Networks is a software system that integrates the content of ten mammalian literature-based interaction network datasets. Filtering to prune low-confidence interactions was implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from “seed” lists of human Entrez gene names. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Genes2Networks is available at http://actin.pharm.mssm.edu/genes2networks.Genes2Network is a powerful web-based software application tool that can help experimental biologists to interpret high-throughput experimental results used in genomics and proteomics studies where the output of these experiments is a list of significantly changing genes or proteins. The system can be used to find relationships between nodes from the seed list, and predict novel nodes that play a key role in a common function. http://precedings.nature.com/documents/35/version/2 Fri, 08 Jun 2007 11:29:03 UTC Genes2Networks: Connecting Lists of Proteins by Using Background Literature-based Mammalian Networks hdl:10101/npre.2007.35.2 2007-06-11 Avi M. Ma'ayan Nature Precedings 2007-06-08T11:29:03Z Manuscript Biotechnology Molecular Cell Biology Bioinformatics http://creativecommons.org/licenses/by/2.5/ http://precedings.nature.com/documents/35/version/1 In recent years, in-silico literature-based mammalian protein-protein interaction network datasets have been developed. These datasets contain binary interactions extracted manually from legacy experimental biomedical research literature. Placing lists of genes or proteins identified as significantly changing in multivariate experiments, in the context of background knowledge about binary interactions, can be used to place these genes or proteins in the context of pathways and protein complexes.Genes2Networks is a software system that integrates the content of ten mammalian literature-based interaction network datasets. Filtering to prune low-confidence interactions was implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from “seed” lists of human Entrez gene names. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Genes2Networks is available at http://actin.pharm.mssm.edu/genes2networks.Genes2Network is a powerful web-based software application tool that can help experimental biologists to interpret high-throughput experimental results used in genomics and proteomics studies where the output of these experiments is a list of significantly changing genes or proteins. The system can be used to find relationships between nodes from the seed list, and predict novel nodes that play a key role in a common function. http://precedings.nature.com/documents/35/version/1 Thu, 07 Jun 2007 11:14:46 UTC Genes2Networks: Connecting Lists of Proteins by Using Background Literature-based Mammalian Networks hdl:10101/npre.2007.35.1 2007-06-11 Avi Ma'ayan Nature Precedings 2007-06-07T11:14:46Z Manuscript Biotechnology Molecular Cell Biology Bioinformatics http://creativecommons.org/licenses/by/2.5/