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Microsoft Dynamics GP users can ensure that their client computers arecurrent on security patches for Microsoft Windows Vista, Windows 7, Windows8, Windows Server 2008, and Windows 2012 by using the Windows Update toolprovided with these systems. Also, if Microsoft Security Update Services isinstalled on the server, much of the update process can be automatedinternally by the organization's IT department.
Hopefully, your budget will allow for a more secure solution that willprotect your corporate data. One such solution is ISA Server. The increasedcost of this additional server provides a great deal more security than atypical consumer firewall, since it usually provides only network addresstranslation (NAT) and packet filtering.
Microsoft SQL Server Reporting Services - To find the service account for SQL Server Reporting Services you'll need to log onto the server where SQL Server Reporting Services is installed, then click on Start, then All Programs, then point to Microsoft SQL Server 2008 (or R2). Then Configuration Tools, then click on Reporting Services Configuration Manager. When this window opens connect to the Reporting Services instance that holds your Microsoft Dynamics GP 2010 R2 reports, then click on the Service Account tab on the left.
Existing ways of accessing data from the Reactome database are limited. Either a researcher is restricted to particular queries defined by a web application programming interface (API), or they have to download the whole database. Reactome Pengine is a web service providing a logic programming based API to the human reactome. This gives researchers greater flexibility in data access than existing APIs, as users can send their own small programs (alongside queries) to Reactome Pengine. The server and an example notebook can be found at -pengine. Source code is available at -pengine and a Docker image is available at . email@example.com. Supplementary data are available at Bioinformatics online.
We announce the public release of the application program interface (API) for the Open Astronomy Catalogs (OACs), the OACAPI. The OACs serve near-complete collections of supernova, tidal disruption, kilonova, and fast stars data (including photometry, spectra, radio, and X-ray observations) via a user-friendly web interface that displays the data interactively and offers full data downloads. The OACAPI, by contrast, enables users to specifically download particular pieces of the OAC dataset via a flexible programmatic syntax, either via URL GET requests, or via a module within the astroquery Python package.
Background Convenient programmatic access to different biological databases allows automated integration of scientific knowledge. Many databases support a function to download files or data snapshots, or a webservice that offers "live" data. However, the functionality that a database offers cannot be represented in a static data download file, and webservices may consume considerable computational resources from the host server. Results MetNetAPI is a versatile Application Programming Interface (API) to the MetNetDB database. It abstracts, captures and retains operations away from a biological network repository and website. A range of database functions, previously only available online, can be immediately (and independently from the website) applied to a dataset of interest. Data is available in four layers: molecular entities, localized entities (linked to a specific organelle), interactions, and pathways. Navigation between these layers is intuitive (e.g. one can request the molecular entities in a pathway, as well as request in what pathways a specific entity participates). Data retrieval can be customized: Network objects allow the construction of new and integration of existing pathways and interactions, which can be uploaded back to our server. In contrast to webservices, the computational demand on the host server is limited to processing data-related queries only. Conclusions An API provides several advantages to a systems biology software platform. MetNetAPI illustrates an interface with a central repository of data that represents the complex interrelationships of a metabolic and regulatory network. As an alternative to data-dumps and webservices, it allows access to a current and "live" database and exposes analytical functions to application developers. Yet it only requires limited resources on the server-side (thin server/fat client setup). The API is available for Java, Microsoft.NET and R programming environments and offers flexible query and broad
ChEBI is a database and ontology of chemical entities of biological interest. It is widely used as a source of identifiers to facilitate unambiguous reference to chemical entities within biological models, databases, ontologies and literature. ChEBI contains a wealth of chemical data, covering over 46,500 distinct chemical entities, and related data such as chemical formula, charge, molecular mass, structure, synonyms and links to external databases. Furthermore, ChEBI is an ontology, and thus provides meaningful links between chemical entities. Unlike many other resources, ChEBI is fully human-curated, providing a reliable, non-redundant collection of chemical entities and related data. While ChEBI is supported by a web service for programmatic access and a number of download files, it does not have an API library to facilitate the use of ChEBI and its data in cheminformatics software. To provide this missing functionality, libChEBI, a comprehensive API library for accessing ChEBI data, is introduced. libChEBI is available in Java, Python and MATLAB versions from , and provides full programmatic access to all data held within the ChEBI database through a simple and documented API. libChEBI is reliant upon the (automated) download and regular update of flat files that are held locally. As such, libChEBI can be embedded in both on- and off-line software applications. libChEBI allows better support of ChEBI and its data in the development of new cheminformatics software. Covering three key programming languages, it allows for the entirety of the ChEBI database to be accessed easily and quickly through a simple API. All code is open access and freely available.
Due to the recent progress of seismograph and communication environment, real-time and continuous ground-motion observation becomes technically and economically feasible. K-NET and KiK-net, which are nationwide strong motion networks operated by NIED, cover all Japan by about 1750 stations in total. More than half of the stations transmit the ground-motion indexes and/or waveform data in every second. Traditionally, strong-motion data were recorded by event-triggering based instruments with non-continues telephone line which is connected only after an earthquake. Though the data from such networks mainly contribute to preparations for future earthquakes, huge amount of real-time data from dense network are expected to directly contribute to the mitigation of ongoing earthquake disasters through, e.g., automatic shutdown plants and helping decision-making for initial response. By generating the distribution map of these indexes and uploading them to the website, we implemented the real-time ground motion monitoring system, Kyoshin (strong-motion in Japanese) monitor. This web service (www.kyoshin.bosai.go.jp) started in 2008 and anyone can grasp the current ground motions of Japan. Though this service provides only ground-motion map in GIF format, to take full advantage of real-time strong-motion data to mitigate the ongoing disasters, digital data are important. We have developed a WebAPI to provide real-time data and related information such as ground motions (5 km-mesh) and arrival times estimated from EEW (earthquake early warning). All response data from this WebAPI are in JSON format and are easy to parse. We also developed Kyoshin monitor application for smartphone, 'Kmoni view' using the API. In this application, ground motions estimated from EEW are overlapped on the map with the observed one-second-interval indexes. The application can playback previous earthquakes for demonstration or disaster drill. In mobile environment, data traffic and battery are
The SEED integrates many publicly available genome sequences into a single resource. The database contains accurate and up-to-date annotations based on the subsystems concept that leverages clustering between genomes and other clues to accurately and efficiently annotate microbial genomes. The backend is used as the foundation for many genome annotation tools, such as the Rapid Annotation using Subsystems Technology (RAST) server for whole genome annotation, the metagenomics RAST server for random community genome annotations, and the annotation clearinghouse for exchanging annotations from different resources. In addition to a web user interface, the SEED also provides Web services based API for programmatic access to the data in the SEED, allowing the development of third-party tools and mash-ups. The currently exposed Web services encompass over forty different methods for accessing data related to microbial genome annotations. The Web services provide comprehensive access to the database back end, allowing any programmer access to the most consistent and accurate genome annotations available. The Web services are deployed using a platform independent service-oriented approach that allows the user to choose the most suitable programming platform for their application. Example code demonstrate that Web services can be used to access the SEED using common bioinformatics programming languages such as Perl, Python, and Java. We present a novel approach to access the SEED database. Using Web services, a robust API for access to genomics data is provided, without requiring large volume downloads all at once. The API ensures timely access to the most current datasets available, including the new genomes as soon as they come online. 2b1af7f3a8