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Found 275 result(s)
Swiss Institute of Bioinformatics (SIB) coordinates research and education in bioinformatics throughout Switzerland and provides bioinformatics services to the national and international research community. ExPASy gives access to numerous repositories and databases of SIB. For example: array map, MetaNetX, SWISS-MODEL and World-2DPAGE, and many others see a list here http://www.expasy.org/resources
Pubchem contains 3 databases. 1. PubChem BioAssay: The PubChem BioAssay Database contains bioactivity screens of chemical substances described in PubChem Substance. It provides searchable descriptions of each bioassay, including descriptions of the conditions and readouts specific to that screening procedure. 2. PubChem Compound: The PubChem Compound Database contains validated chemical depiction information provided to describe substances in PubChem Substance. Structures stored within PubChem Compounds are pre-clustered and cross-referenced by identity and similarity groups. 3. PubChem Substance. The PubChem Substance Database contains descriptions of samples, from a variety of sources, and links to biological screening results that are available in PubChem BioAssay. If the chemical contents of a sample are known, the description includes links to PubChem Compound.
eCrystals - Southampton is the archive for Crystal Structures generated by the Southampton Chemical Crystallography Group and the EPSRC UK National Crystallography Service.
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>>>!!!<<< The repository is no longer available. >>>!!!<<< Indian Genetic Disease Database (IGDD) is an initiative of CSIR Indian Institute of Chemical Biology. It is supported by Council of Scientific and Industrial Research (CSIR) and Department of Biotechnology (DBT) of India. The Indian people represent one-sixth of the world population and consists of a ethnically, geographically, and genetically diverse population. In some communities the ratio of genetic disorder is relatively high due to consanguineous marriage practiced in the community. This database has been created to keep track of mutations in the causal genes for genetic diseases common in India and help the physicians, geneticists, and other professionals retrieve and use the information for the benefit of the public. The database includes scientific information about these genetic diseases and disabilities, but also statistical information about these diseases in today's society. Data is categorized by body part affected and then by title of the disease.
The centerpiece of the Global Trade Analysis Project is a global data base describing bilateral trade patterns, production, consumption and intermediate use of commodities and services. The GTAP Data Base consists of bilateral trade, transport, and protection matrices that link individual country/regional economic data bases. The regional data bases are derived from individual country input-output tables, from varying years.
>>>!!!<<< 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.
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The German Neuroinformatics Node's data infrastructure (GIN) services provide a platform for comprehensive and reproducible management and sharing of neuroscience data. Building on well established versioning technology, GIN offers the power of a web based repository management service combined with a distributed file storage. The service addresses the range of research data workflows starting from data analysis on the local workstation to remote collaboration and data publication.
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The RAMEDIS system is a platform independent, web-based information system for rare metabolic diseases based on filed case reports. It was developed in close cooperation with clinical partners to allow them to collect information on rare metabolic diseases with extensive details, e.g. about occurring symptoms, laboratory findings, therapy and molecular data.
The Durham High Energy Physics Database (HEPData), formerly: the Durham HEPData Project, has been built up over the past four decades as a unique open-access repository for scattering data from experimental particle physics. It currently comprises the data points from plots and tables related to several thousand publications including those from the Large Hadron Collider (LHC). The Durham HepData Project has for more than 25 years compiled the Reactions Database containing what can be loosly described as cross sections from HEP scattering experiments. The data comprise total and differential cross sections, structure functions, fragmentation functions, distributions of jet measures, polarisations, etc... from a wide range of interactions. In the new HEPData site (hepdata.net), you can explore new functionalities for data providers and data consumers, as well as the submission interface. HEPData is operated by CERN and IPPP at Durham University and is based on the digital library framework Invenio.
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The Health Atlas is an alliance of medical ontologists, medical systems biologists and clinical trials groups to design and implement a multi-functional and quality-assured atlas. It provides models, data and metadata on specific use cases from medical research projects from the partner institutions.
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The TRR228DB is the project-database of the Collaborative Research Centre 228 "Future Rural Africa: Future-making and social-ecological transformation" (CRC/Transregio 228, https://www.crc228.de) funded by the German Research Foundation (DFG, German Research Foundation – Project number 328966760). The project-database is a new implementation of the TR32DB and online since 2018. It handles all data including metadata, which are created by the involved project participants from several institutions (e.g. Universities of Cologne and Bonn) and research fields (e.g. anthropology, agroeconomics, ecology, ethnology, geography, politics and soil sciences). The data is resulting from several field campaigns, interviews, surveys, remote sensing, laboratory studies and modelling approaches. Furthermore, outcomes of the scientists such as publications, conference contributions, PhD reports and corresponding images are collected.
Water DAMS (Water Data Analysis and Management System) provides access to foundational water treatment technology data that enable researchers and decision-makers to identify and quantify opportunities for technology innovations to reduce the cost and energy intensity of desalination. It is the submission point for all data generated by research conducted by the National Alliance for Water Innovation (NAWI) and is designed to be used by the broader water research community. With publicly accessible contributions from a variety of academic and industrial partners, Water DAMS seeks to enable data discoverability, improve accessibility, and accelerate collaboration that contributes to pipe parity and innovation in water treatment technologies.
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NODE (The National Omics Data Encyclopedia) provides an integrated, compatible, comparable, and scalable multi-omics resource platform that supports flexible data management and effective data release. NODE uses a hierarchical data architecture to support storage of muti-omics data including sequencing data, MS based proteomics data, MS or NMR based metabolomics data, and fluorescence imaging data. Launched in early 2017, NODE has collected and published over 900 terabytes of omics data for researchers from China and all over the world in last three years, 22% of which contains multiple omics data. NODE provides functions around the whole life cycle of omics data, from data archive, data requests/responses to data sharing, data analysis, data review and publish.
OBIS strives to document the ocean's diversity, distribution and abundance of life. Created by the Census of Marine Life, OBIS is now part of the Intergovernmental Oceanographic Commission (IOC) of UNESCO, under its International Oceanographic Data and Information Exchange (IODE) programme
SeaBASS, the publicly shared archive of in situ oceanographic and atmospheric data maintained by the NASA Ocean Biology Processing Group (OBPG). High quality in situ measurements are prerequisite for satellite data product validation, algorithm development, and many climate-related inquiries. As such, the NASA Ocean Biology Processing Group (OBPG) maintains a local repository of in situ oceanographic and atmospheric data to support their regular scientific analyses. The SeaWiFS Project originally developed this system, SeaBASS, to catalog radiometric and phytoplankton pigment data used their calibration and validation activities. To facilitate the assembly of a global data set, SeaBASS was expanded with oceanographic and atmospheric data collected by participants in the SIMBIOS Program, under NASA Research Announcements NRA-96 and NRA-99, which has aided considerably in minimizing spatial bias and maximizing data acquisition rates. Archived data include measurements of apparent and inherent optical properties, phytoplankton pigment concentrations, and other related oceanographic and atmospheric data, such as water temperature, salinity, stimulated fluorescence, and aerosol optical thickness. Data are collected using a number of different instrument packages, such as profilers, buoys, and hand-held instruments, and manufacturers on a variety of platforms, including ships and moorings.
DaSCH is the trusted platform and partner for open research data in the Humanities. DaSCH develops and operates a FAIR long-term repository and a generic virtual research environment for open research data in the humanities in Switzerland. We provide long-term direct access to the data, enable their continuous editing and allow for precise citation of single objects within a dataset. We ensure interoperability with tools used by the Humanities and Cultural Sciences communities and foster the use of standards. The development of our platform happens in close cooperation with these communities. We provide training and advice in the area of research data management, promote open data and the use of standards. DaSCH is the coordinating institution and representative of Switzerland in the European Research Infrastructure Consortium ‘Digital Research Infrastructure for the Arts and Humanities’ (DARIAH ERIC). Within this mandate, we actively engage in community building within Switzerland and abroad. DaSCH cooperates with national and international organizations and initiatives in order to provide services that are fit for purpose within the broader Swiss open research data landscape and that are coordinated with other institutions such as FORS. We base our actions on the values reliability, flexibility, appreciation, curiosity, and persistence. Furthermore, DARIAH’s activities in Switzerland are coordinated by DaSCH and DaSCH is acting as DARIAH-CH Coordination Office.
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BExIS is the online data repository and information system of the Biodiversity Exploratories Project (BE). The BE is a German network of biodiversity related working groups from areas such as vegetation and soil science, zoology and forestry. Up to three years after data acquisition, the data use is restricted to members of the BE. Thereafter, the data is usually public available (https://www.bexis.uni-jena.de/ddm/publicsearch/index).
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The Atlantic Canada Conservation Data Centre (ACCDC) maintains comprehensive lists of plant and animal species. The Atlantic CDC has geo-located records of species occurrences and records of extremely rare to uncommon species in the Atlantic region, including New Brunswick, Nova Scotia, Prince Edward Island, Newfoundland, and Labrador. The Atlantic CDC also maintains biological and other types of data in a variety of linked databases.
Stanford Network Analysis Platform (SNAP) is a general purpose network analysis and graph mining library. It is written in C++ and easily scales to massive networks with hundreds of millions of nodes, and billions of edges. It efficiently manipulates large graphs, calculates structural properties, generates regular and random graphs, and supports attributes on nodes and edges. SNAP is also available through the NodeXL which is a graphical front-end that integrates network analysis into Microsoft Office and Excel. The SNAP library is being actively developed since 2004 and is organically growing as a result of our research pursuits in analysis of large social and information networks. Largest network we analyzed so far using the library was the Microsoft Instant Messenger network from 2006 with 240 million nodes and 1.3 billion edges. The datasets available on the website were mostly collected (scraped) for the purposes of our research. The website was launched in July 2009.
dbEST is a division of GenBank that contains sequence data and other information on "single-pass" cDNA sequences, or "Expressed Sequence Tags", from a number of organisms. Expressed Sequence Tags (ESTs) are short (usually about 300-500 bp), single-pass sequence reads from mRNA (cDNA). Typically they are produced in large batches. They represent a snapshot of genes expressed in a given tissue and/or at a given developmental stage. They are tags (some coding, others not) of expression for a given cDNA library. Most EST projects develop large numbers of sequences. These are commonly submitted to GenBank and dbEST as batches of dozens to thousands of entries, with a great deal of redundancy in the citation, submitter and library information. To improve the efficiency of the submission process for this type of data, we have designed a special streamlined submission process and data format. dbEST also includes sequences that are longer than the traditional ESTs, or are produced as single sequences or in small batches. Among these sequences are products of differential display experiments and RACE experiments. The thing that these sequences have in common with traditional ESTs, regardless of length, quality, or quantity, is that there is little information that can be annotated in the record. If a sequence is later characterized and annotated with biological features such as a coding region, 5'UTR, or 3'UTR, it should be submitted through the regular GenBank submissions procedure (via BankIt or Sequin), even if part of the sequence is already in dbEST. dbEST is reserved for single-pass reads. Assembled sequences should not be submitted to dbEST. GenBank will accept assembled EST submissions for the forthcoming TSA (Transcriptome Shotgun Assembly) division. The individual reads which make up the assembly should be submitted to dbEST, the Trace archive or the Short Read Archive (SRA) prior to the submission of the assemblies.
The Gene database provides detailed information for known and predicted genes defined by nucleotide sequence or map position. Gene supplies gene-specific connections in the nexus of map, sequence, expression, structure, function, citation, and homology data. Unique identifiers are assigned to genes with defining sequences, genes with known map positions, and genes inferred from phenotypic information. These gene identifiers are used throughout NCBI's databases and tracked through updates of annotation. Gene includes genomes represented by NCBI Reference Sequences (or RefSeqs) and is integrated for indexing and query and retrieval from NCBI's Entrez and E-Utilities systems.
<<<!!!<<< CRAWDAD has moved to IEEE-Dataport https://www.re3data.org/repository/r3d100012569 The datasets in the Community Resource for Archiving Wireless Data at Dartmouth (CRAWDAD) repository are now hosted as the CRAWDAD Collection on IEEE Dataport. After nearly two decades as a stand-alone archive at crawdad.org, the migration of the collection to IEEE DataPort provides permanence and new visibility. >>>!!!>>>
This Animal Quantitative Trait Loci (QTL) database (Animal QTLdb) is designed to house all publicly available QTL and trait mapping data (i.e. trait and genome location association data; collectively called "QTL data" on this site) on livestock animal species for easily locating and making comparisons within and between species. New database tools are continuely added to align the QTL and association data to other types of genome information, such as annotated genes, RH / SNP markers, and human genome maps. Besides the QTL data from species listed below, the QTLdb is open to house QTL/association date from other animal species where feasible. Note that the JAS along with other journals, now require that new QTL/association data be entered into a QTL database as part of their publication requirements.
The Plant Metabolic Network (PMN) provides a broad network of plant metabolic pathway databases that contain curated information from the literature and computational analyses about the genes, enzymes, compounds, reactions, and pathways involved in primary and secondary metabolism in plants. The PMN currently houses one multi-species reference database called PlantCyc and 22 species/taxon-specific databases.