64 resultados para Network-based


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A major problem in developmental neurotoxicity (DNT) risk assessment is the lack of toxicological hazard information for most compounds. Therefore, new approaches are being considered to provide adequate experimental data that allow regulatory decisions. This process requires a matching of regulatory needs on the one hand and the opportunities provided by new test systems and methods on the other hand. Alignment of academically and industrially driven assay development with regulatory needs in the field of DNT is a core mission of the International STakeholder NETwork (ISTNET) in DNT testing. The first meeting of ISTNET was held in Zurich on 23-24 January 2014 in order to explore the concept of adverse outcome pathway (AOP) to practical DNT testing. AOPs were considered promising tools to promote test systems development according to regulatory needs. Moreover, the AOP concept was identified as an important guiding principle to assemble predictive integrated testing strategies (ITSs) for DNT. The recommendations on a road map towards AOP-based DNT testing is considered a stepwise approach, operating initially with incomplete AOPs for compound grouping, and focussing on key events of neurodevelopment. Next steps to be considered in follow-up activities are the use of case studies to further apply the AOP concept in regulatory DNT testing, making use of AOP intersections (common key events) for economic development of screening assays, and addressing the transition from qualitative descriptions to quantitative network modelling.

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The article discusses the development of WEBDATANET established in 2011 which aims to create a multidisciplinary network of web-based data collection experts in Europe. Topics include the presence of 190 experts in 30 European countries and abroad, the establishment of web-based teaching and discussion platforms and working groups and task forces. Also discussed is the scope of the research carried by WEBDATANET. In light of the growing importance of web-based data in the social and behavioral sciences, WEBDATANET was established in 2011 as a COST Action (IS 1004) to create a multidisciplinary network of web-based data collection experts: (web) survey methodologists, psychologists, sociologists, linguists, economists, Internet scientists, media and public opinion researchers. The aim was to accumulate and synthesize knowledge regarding methodological issues of web-based data collection (surveys, experiments, tests, non-reactive data, and mobile Internet research), and foster its scientific usage in a broader community.

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Defects in FAM161A, a protein of unknown function localized at the cilium of retinal photoreceptor cells, cause retinitis pigmentosa, a form of hereditary blindness. By using different fragments of this protein as baits to screen cDNA libraries of human and bovine retinas, we defined a yeast two-hybrid-based FAM161A interactome, identifying 53 bona fide partners. In addition to statistically significant enrichment in ciliary proteins, as expected, this interactome revealed a substantial bias towards proteins from the Golgi apparatus, the centrosome and the microtubule network. Validation of interaction with key partners by co-immunoprecipitation and proximity ligation assay confirmed that FAM161A is a member of the recently recognized Golgi-centrosomal interactome, a network of proteins interconnecting Golgi maintenance, intracellular transport and centrosome organization. Notable FAM161A interactors included AKAP9, FIP3, GOLGA3, KIFC3, KLC2, PDE4DIP, NIN and TRIP11. Furthermore, analysis of FAM161A localization during the cell cycle revealed that this protein followed the centrosome during all stages of mitosis, likely reflecting a specific compartmentalization related to its role at the ciliary basal body during the G0 phase. Altogether, these findings suggest that FAM161A's activities are probably not limited to ciliary tasks but also extend to more general cellular functions, highlighting possible novel mechanisms for the molecular pathology of retinal disease.

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Defining digital humanities might be an endless debate if we stick to the discussion about the boundaries of this concept as an academic "discipline". In an attempt to concretely identify this field and its actors, this paper shows that it is possible to analyse them through Twitter, a social media widely used by this "community of practice". Based on a network analysis of 2,500 users identified as members of this movement, the visualisation of the "who's following who?" graph allows us to highlight the structure of the network's relationships, and identify users whose position is particular. Specifically, we show that linguistic groups are key factors to explain clustering within a network whose characteristics look similar to a small world.