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Found 25 result(s)
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IntEnz contains the recommendation of the Nomenclature Committee of the International Union of Biochemistry and Molecular Biology on the nomenclature and classification of enzyme-catalyzed reactions. Users can browse by enzyme classification or use advanced search options to search enzymes by class, subclass and sub-subclass information.
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PSnpBind is a large database of protein–ligand complexes covering a wide range of binding pocket mutations and small molecules’ landscape. This database can be used as a source of data for different types of studies, for example, developing machine learning algorithms to predict protein–ligand affinity or mutation's effect on it which requires an extensive amount of data with a wide coverage of mutation types and small molecules. Also, studies of protein-ligand interactions and conformer orientation changes across different mutated versions of a protein can be established using data from PSnpBind.
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<<<!!!<<< DTU Bioinformatics was closed on 31 December 2018 as part of a reorganization at DTU >>>!!!>>>
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ArachnoServer is a manually curated database containing information on the sequence, three-dimensional structure, and biological activity of protein toxins derived from spider venom. Spiders are the largest group of venomous animals and they are predicted to contain by far the largest number of pharmacologically active peptide toxins (Escoubas et al., 2006). ArachnoServer has been custom-built so that a wide range of biological scientists, including neuroscientists, pharmacologists, and toxinologists, can readily access key data relevant to their discipline without being overwhelmed by extraneous information.
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GermOnline 4.0 is a cross-species database gateway focusing on high-throughput expression data relevant for germline development, the meiotic cell cycle and mitosis in healthy versus malignant cells. The portal provides access to the Saccharomyces Genomics Viewer (SGV) which facilitates online interpretation of complex data from experiments with high-density oligonucleotide tiling microarrays that cover the entire yeast genome.
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>>>!!!<<< OMICtools is no longer online >>>!!!<<<
We founded OMICtools in 2012 with the vision to drive progress in life science. We wanted to empower life science practitioners all over the world to achieve breakthroughs by getting data to talk. While we made tremendous progress over the past three years, developing a bioinformatics database of software and dynamic protocols, attracting more than 1.5M visitors a year, we lacked the financial support we needed to continue. We certainly gave it our all. We'd like to thank everyone who believed in us and supported us on this journey: all our users, our community, our friends, families and employees (who we consider as our extended family!).
omicX will probably shut down its operations within the next few weeks. The team and I remain firmly committed to our vision, particularly at this very difficult time. It is now, more than ever before, that researchers need access to a resource that pools collective scientific intelligence. We have accumulated an awful lot of experience which we are keen to share. If your institution would be interested in taking over our website and database, to provide researchers with continued access to the platform, or you simply want to stay in touch with the omicX team, contact us at contact@omictools.com or at carine.toutain@fhbx.eu.
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DDBJ; DNA Data Bank of Japan is the sole nucleotide sequence data bank in Asia, which is officially certified to collect nucleotide sequences from researchers and to issue the internationally recognized accession number to data submitters.Since we exchange the collected data with EMBL-Bank/EBI; European Bioinformatics Institute and GenBank/NCBI; National Center for Biotechnology Information on a daily basis, the three data banks share virtually the same data at any given time. The virtually unified database is called "INSD; International Nucleotide Sequence Database DDBJ collects sequence data mainly from Japanese researchers, but of course accepts data and issue the accession number to researchers in any other countries.
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The Antimicrobial Peptide Database (APD) was originally created by a graduate student, Zhe Wang, as his master's thesis in the laboratory of Dr. Guangshun Wang. The project was initiated in 2002 and the first version of the database was open to the public in August 2003. It contained 525 peptide entries, which can be searched in multiple ways, including APD ID, peptide name, amino acid sequence, original location, PDB ID, structure, methods for structural determination, peptide length, charge, hydrophobic content, antibacterial, antifungal, antiviral, anticancer, and hemolytic activity. Some results of this bioinformatics tool were reported in the 2004 database paper. The peptide data stored in the APD were gleaned from the literature (PubMed, PDB, Google, and Swiss-Prot) manually in over a decade.
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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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M-CSA is a database of enzyme reaction mechanisms. It provides annotation on the protein, catalytic residues, cofactors, and the reaction mechanisms of hundreds of enzymes. There are two kinds of entries in M-CSA. 'Detailed mechanism' entries are more complete and show the individual chemical steps of the mechanism as schemes with electron flow arrows. 'Catalytic Site' entries annotate the catalytic residues necessary for the reaction, but do not show the mechanism. The M-CSA (Mechanism and Catalytic Site Atlas) represents a unified resource that combines the data in both MACiE and the CSA
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SureChemOpen is a free resource for researchers who want to search, view and link to patent chemistry. For end-users with professional search and analysis needs, we offer the fully-featured SureChemPro. For enterprise users, SureChemDirect provides all our patent chemistry via an API or a data feed. The SureChem family of products is built upon the Claims® Global Patent Database, a comprehensive international patent collection provided by IFI Claims®. This state of the art database is normalized and curated to provide unprecedented consistency and quality.
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STRING is a database of known and predicted protein interactions.
The interactions include direct (physical) and indirect (functional) associations; they are derived from four sources:
- Genomic Context
- High-throughput Experiments
- (Conserved) Coexpression
- Previous Knowledge
STRING quantitatively integrates interaction data from these sources for a large number of organisms, and transfers information between these organisms where applicable.
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The Complex Portal is a manually curated, encyclopaedic resource of macromolecular complexes from a number of key model organisms, entered into the IntAct molecular interaction database (https://www.ebi.ac.uk/intact/). Data includes protein-only complexes as well as protein-small molecule and protein-nucleic acid complexes. All complexes are derived from physical molecular interaction evidences extracted from the literature and cross-referenced in the entry, or by curator inference from information on homologs in closely related species or by inference from scientific background. All complexes are tagged with Evidence and Conclusion Ontology codes to indicate the type of evidence available for each entry.
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The IMGT/PRIMER-DB database provides standardized information on oligonucleotides or primers of the immunoglobulins (IG) and T cell receptors (TR).
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The MEROPS database is an information resource for peptidases (also termed proteases, proteinases and proteolytic enzymes) and the proteins that inhibit them.
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ArrayExpress is one of the major international repositories for high-throughput functional genomics data from both microarray and high-throughput sequencing studies, many of which are supported by peer-reviewed publications. Data sets are submitted directly to ArrayExpress and curated by a team of specialist biological curators. In the past (until 2018) datasets from the NCBI Gene Expression Omnibus database were imported on a weekly basis. Data is collected to MIAME and MINSEQE standards.
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<<<!!!<<< This repository is no longer available. >>>!!!>>> A human interactome map. The sequencing of the human genome has provided a surprisingly small number of genes, indicating that the complex organization of life is not reflected in the gene number but, rather, in the gene products – that is, in the proteins. These macromolecules regulate the vast majority of cellular processes by their ability to communicate with each other and to assemble into larger functional units. Therefore, the systematic analysis of protein-protein interactions is fundamental for the understanding of protein function, cellular processes and, ultimately, the complexity of life. Moreover, interactome maps are particularly needed to link new proteins to disease pathways and the identification of novel drug targets.
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The GWAS Catalog is an open access repository of all human genome wide association studies. It is considered the “go-to” resource for genetic evidence of associations between common genetic variation and diseases or phenotypes, is accessed by scientists, clinicians and other users worldwide, and is integrated with numerous other resources. Association data and metadata are identified and extracted from the scientific literature by expert data curators. Submissions of full genome wide summary data can be made directly by authors, either before or after journal publication.
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The COVID-19 Data Portal was launched in April 2020 to bring together relevant datasets for sharing and analysis in an effort to accelerate coronavirus research. It enables researchers to upload, access and analyse COVID-19 related reference data and specialist datasets as part of the wider European COVID-19 Data Platform.
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>>>>!!!!<<<< The Cancer Genomics Hub mission is now completed.
The Cancer Genomics Hub was established in August 2011 to provide a repository to The Cancer Genome Atlas, the childhood cancer initiative Therapeutically Applicable Research to Generate Effective Treatments and the Cancer Genome Characterization Initiative.
CGHub rapidly grew to be the largest database of cancer genomes in the world, storing more than 2.5 petabytes of data and serving downloads of nearly 3 petabytes per month.
As the central repository for the foundational genome files, CGHub streamlined team science efforts as data became as easy to obtain as downloading from a hard drive.
The convenient access to Big Data, and the collaborations that CGHub made possible, are now essential to cancer research. That work continues at the NCI's Genomic Data Commons. All files previously stored at CGHub can be found there.
The Website for the Genomic Data Commons is here: https://gdc.nci.nih.gov/ >>>>!!!!<<<<
The Cancer Genomics Hub (CGHub) is a secure repository for storing, cataloging, and accessing cancer genome sequences, alignments, and mutation information from the Cancer Genome Atlas (TCGA) consortium and related projects.
Access to CGHub Data: All researchers using CGHub must meet the access and use criteria established by the National Institutes of Health (NIH) to ensure the privacy, security, and integrity of participant data. CGHub also hosts some publicly available data, in particular data from the Cancer Cell Line Encyclopedia. All metadata is publicly available and the catalog of metadata and associated BAMs can be explored using the CGHub Data Browser.
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BRENDA is the main collection of enzyme functional data available to the scientific community worldwide. The enzymes are classified according to the Enzyme Commission list of enzymes. It is available free of charge for via the internet (http://www.brenda-enzymes.org/) and as an in-house database for commercial users (requests to our distributor Biobase). The enzymes are classified according to the Enzyme Commission list of enzymes. Some 5000 "different" enzymes are covered. Frequently enzymes with very different properties are included under the same EC number. BRENDA includes biochemical and molecular information on classification, nomenclature, reaction, specificity, functional parameters, occurrence, enzyme structure, application, engineering, stability, disease, isolation, and preparation. The database also provides additional information on ligands, which function as natural or in vitro substrates/products, inhibitors, activating compounds, cofactors, bound metals, and other attributes.
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The mission of the GO Consortium is to develop a comprehensive, computational model of biological systems, ranging from the molecular to the organism level, across the multiplicity of species in the tree of life.
The Gene Ontology (GO) knowledgebase is the world’s largest source of information on the functions of genes. This knowledge is both human-readable and machine-readable, and is a foundation for computational analysis of large-scale molecular biology and genetics experiments in biomedical research.
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The Cellosaurus is a knowledge resource on cell lines. It attempts to describe all cell lines used in biomedical research. Its scope includes: Immortalized cell lines, Naturally immortal cell lines (example: stem cell lines), Finite life cell lines when those are distributed and used widely, Vertebrate cell line with an emphasis on human, mouse and rat cell lines, Invertebrate (insects and ticks) cell lines. Its scope does not include: Primary cell lines (with the exception of the finite life cell lines described above), Plant cell lines. Cellosaurus was initiated to be used as a cell line controlled vocabulary in the context of the neXtProt knowledgebase, but it quickly become apparent that there was a need for a cell line knowledge resource that would serve the needs of individual researchers, cell line distributors and bioinformatic resources. This leads to an increase of the scope and depth of the content of the Cellosaurus. The Cellosaurus is a participant of the Resource Identification Initiative and contributes actively to the work of the International Cell Line Authentication Committee (ICLAC). It is a Global Core Biodata Resource, an ELIXIR Core Data Resource and an IRDiRC Recognized Resource.
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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.
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- Animal Ecology, Biodiversity and Ecosystem Research
- Hydrogeology, Hydrology, Limnology, Urban Water Management, Water Chemistry, Integrated Water Resources Management
- Basic Forest Research
- Ecology of Agricultural Landscapes
- Soil Sciences
- Plant Ecology and Ecosystem Analysis
- Bioinformatics and Theoretical Biology
- Biochemistry
- Zoology
- Biology
- Life Sciences
- Water Research
- Geosciences (including Geography)
- Natural Sciences
- Agriculture, Forestry, Horticulture and Veterinary Medicine
- Agriculture, Forestry, Horticulture and Veterinary Medicine
- Plant Sciences
- Basic Biological and Medical Research
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DEIMS-SDR (Dynamic Ecological Information Management System - Site and dataset registry) is an information management system that allows you to discover long-term ecosystem research sites around the globe, along with the data gathered at those sites and the people and networks associated with them. DEIMS-SDR describes a wide range of sites, providing a wealth of information, including each site’s location, ecosystems, facilities, parameters measured and research themes. It is also possible to access a growing number of datasets and data products associated with the sites. All sites and dataset records can be referenced using unique identifiers that are generated by DEIMS-SDR. It is possible to search for sites via keyword, predefined filters or a map search. By including accurate, up to date information in DEIMS, site managers benefit from greater visibility for their LTER site, LTSER platform and datasets, which can help attract funding to support site investments. The aim of DEIMS-SDR is to be the globally most comprehensive catalogue of environmental research and monitoring facilities, featuring foremost but not exclusively information about all LTER sites on the globe and providing that information to science, politics and the public in general.
- Current projects
- EOSC FAIR-IMPACT
- re3data COREF
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To the extent possible under law,
re3data.org
has waived all copyright and related or neighboring rights to
the database entries of re3data.org.
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Except where otherwise noted, content on this site is licensed under a
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- Cite this service: re3data.org - Registry of Research Data Repositories. https://doi.org/10.17616/R3D last accessed: 2024-05-25
