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Found 7 result(s)
>>>!!!<<< The repository is no longer available. >>>!!!<<< Here you will find a collection of atomic microstructures that have been built by the atomic modeling community. Feel free to download any of these and use them in your own scientific explorations.The focus of this cyberinfrastructure is to advance the field of atomic-scale modeling of materials by acting as a forum for disseminating new atomistic scale methodologies, educating non-experts and the next generation of computational materials scientists, and serving as a bridge between the atomistic and complementary (electronic structure, mesoscale) modeling communities.
BioSimulations is a web application for sharing and re-using biomodels, simulations, and visualizations of simulations results. BioSimulations supports a wide range of modeling frameworks (e.g., kinetic, constraint-based, and logical modeling), model formats (e.g., BNGL, CellML, SBML), and simulation tools (e.g., COPASI, libRoadRunner/tellurium, NFSim, VCell). BioSimulations aims to help researchers discover published models that might be useful for their research and quickly try them via a simple web-based interface.
VIPERdb is a database for icosahedral virus capsid structures . The emphasis of the resource is on providing data from structural and computational analyses on these systems, as well as high quality renderings for visual exploration. In addition, all virus capsids are placed in a single icosahedral orientation convention, facilitating comparison between different structures. The web site includes powerful search utilities , links to other relevant databases, background information on virus capsid structure, and useful database interface tools.
The DesignSafe Data Depot Repository (DDR) is the platform for curation and publication of datasets generated in the course of natural hazards research. The DDR is an open access data repository that enables data producers to safely store, share, organize, and describe research data, towards permanent publication, distribution, and impact evaluation. The DDR allows data consumers to discover, search for, access, and reuse published data in an effort to accelerate research discovery. It is a component of the DesignSafe cyberinfrastructure, which represents a comprehensive research environment that provides cloud-based tools to manage, analyze, curate, and publish critical data for research to understand the impacts of natural hazards. DesignSafe is part of the NSF-supported Natural Hazards Engineering Research Infrastructure (NHERI), and aligns with its mission to provide the natural hazards research community with open access, shared-use scholarship, education, and community resources aimed at supporting civil and social infrastructure prior to, during, and following natural disasters. It serves a broad national and international audience of natural hazard researchers (both engineers and social scientists), students, practitioners, policy makers, as well as the general public. It has been in operation since 2016, and also provides access to legacy data dating from about 2005. These legacy data were generated as part of the NSF-supported Network for Earthquake Engineering Simulation (NEES), a predecessor to NHERI. Legacy data and metadata belonging to NEES were transferred to the DDR for continuous preservation and access.
This is CSDB version 1 merged from Bacterial (BCSDB) and Plant&Fungal (PFCSDB) databases. This database aims at provision of structural, bibliographic, taxonomic, NMR spectroscopic and other information on glycan and glycoconjugate structures of prokaryotic, plant and fungal origin. It has been merged from the Bacterial and Plant&Fungal Carbohydrate Structure Databases (BCSDB+PFCSDB). The key points of this service are: High coverage. The coverage for bacteria (up to 2016) and archaea (up to 2016) is above 80%. Similar coverage for plants and fungi is expected in the future. The database is close to complete up to 1998 for plants, and up to 2006 for fungi. Data quality. High data quality is achieved by manual curation using original publications which is assisted by multiple automatic procedures for error control. Errors present in publications are reported and corrected, when possible. Data from other databases are verified on import. Detailed annotations. Structural data are supplied with extended bibliography, assigned NMR spectra, taxon identification including strains and serogroups, and other information if available in the original publication. Services. CSDB serves as a platform for a number of computational services tuned for glycobiology, such as NMR simulation, automated structure elucidation, taxon clustering, 3D molecular modeling, statistical processing of data etc. Integration. CSDB is cross-linked to other glycoinformatics projects and NCBI databases. The data are exportable in various formats, including most widespread encoding schemes and records using GlycoRDF ontology. Free web access. Users can access the database for free via its web interface (see Help). The main source of data is retrospective literature analysis. About 20% of data were imported from CCSD (Carbbank, University of Georgia, Athens; structures published before 1996) with subsequent manual curation and approval. The current coverage is displayed in red on the top of the left menu. The time lag between the publication of new data and their deposition into CSDB is ca. 1 year. In the scope of bacterial carbohydrates, CSDB covers nearly all structures of this origin published up to 2016. Prokaryotic, plant and fungal means that a glycan was found in the organism(s) belonging to these taxonomic domains or was obtained by modification of those found in them. Carbohydrate means a structure composed of any residues linked by glycosidic, ester, amidic, ketal, phospho- or sulpho-diester bonds in which at least one residue is a sugar or its derivative.
The SuiteSparse Matrix Collection is a large and actively growing set of sparse matrices that arise in real applications. The Collection is widely used by the numerical linear algebra community for the development and performance evaluation of sparse matrix algorithms. It allows for robust and repeatable experiments. Its matrices cover a wide spectrum of domains, include those arising from problems with underlying 2D or 3D geometry (as structural engineering, computational fluid dynamics, model reduction, electromagnetics, semiconductor devices, thermodynamics, materials, acoustics, computer graphics/vision, robotics/kinematics, and other discretizations) and those that typically do not have such geometry (optimization, circuit simulation, economic and financial modeling, theoretical and quantum chemistry, chemical process simulation, mathematics and statistics, power networks, and other networks and graphs.