eNanoMapper - A Database and Ontology Framework fo.. (ENANOMAPPER)
eNanoMapper - A Database and Ontology Framework for Nanomaterials Design and Safety Assessment
Date du début: 1 févr. 2014,
Date de fin: 31 janv. 2017
eNanoMapper will develop a data management and analysis infrastructure together with ontologies supporting the safety assessment activities of the European Nanomaterials research and development community. The project will address the requirements of safety assessment of nanomaterials by providing databases, analysis tools and ontologies for risk assessment and linking them with existing resources in this area.The project plan involves close cooperation with NanoSafety Cluster members and other international organisations such as OECD, ISO/CEN, EC JRC, and EChA. Their requirements will guide the development of tools for experimental design, model building, and meta analysis across multiple datasets.An ontology for nanomaterials will be developed to provide the following features: annotation of nanostructures and relevant biological properties, annotation of experimental model systems (e.g. cell lines), conditions, and protocols, complex search and reasoning capabilities, and the integration of data from existing nanotoxicology sources.Systematic physicochemical, geometrical, structural, and biological studies of nanomaterials are nearly absent in the public domain. The establishment of a universal standardisation schema and infrastructure for nanomaterials safety assessment is a key project goal. It should catalyze collaboration, integrated analysis, and discoveries from data organised within a knowledge-based framework. It will support the discovery of nanomaterial properties responsible for toxicity, the identification of toxicity pathways and nano-bio interactions from linked datasets, ontologies, omics data and external data sources.By interfacing with statistical and data mining tools we will be able to provide scientifically sound guidelines for experimental design as well as computational models for predicting nanotoxicity. These computational models will help to design safe nanomaterials and improve the risk assessment of existing nanoparticles.
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