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Found 258 result(s)
4TU.ResearchData, previously known as 4TU.Centre for Research Data, is a research data repository dedicated to the science, engineering and design disciplines. It offers the knowledge, experience and the tools to manage, publish and find scientific research data in a standardized, secure and well-documented manner. 4TU.ResearchData provides the research community with: Customised advice and support on research data management; A long-term repository for scientific research data; Support for current research projects; Tools to enhance reuse of research data.
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<<<!!!<<< As stated 2017-11-23 the database is not available anymore >>>!!!>>> ACEpepDB is a database ran by the Central Food Technological Research Institute. It contains records of about 865 peptides. Each record provides information on the food source, preparation, purification and any other additional information. Each record includes the reference(s). The database provides a search and browsing option for a more personalized research experience.
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TERN's AEKOS data portal is the original gateway to Australian ecology data. It is a ‘data and research methods’ data portal for Australia’s land-dwelling plants, animals and their environments. The primary focus of data content is raw co-located ‘species and environment’ ecological survey data that has been collected at the ‘plot’ level to describe biodiversity, its patterns and ecological processes. It is openly accessible with standard discovery metadata and user-oriented, contextual metadata critical for data reuse. Our services support the ecosystem science community, land managers and governments seeking to publish under COPE publishing ethics and the FAIR data publishing principles. AEKOS is registered with Thomson & Reuters Data Citation Index and is a recommended repository of Nature Publishing’s Scientific Data. There are currently 97,037 sites covering mostly plant biodiversity and co-located environmental data of Australia. The AEKOS initiative is supported by TERN (tern.org.au), hosted by The University of Adelaide and funded by the Australian Government’s National Research Infrastructure for Australia.
We are working on a new version of ALFRED web interface. The current web interface will not be available from December 15th, 2023. There will be a period where a public web interface is not available for viewing ALFRED data. Expected date for the deployment of the new ALFRED web interface with minimum functions is March 1st, 2024 --------------------------------------------- ALFRED is a free, web-accessible, curated compilation of allele frequency data on DNA sequence polymorphisms in anthropologically defined human populations. ALFRED is distinct from such databases as dbSNP, which catalogs sequence variation.
The Allele Frequency Net Database (AFND) is a public database which contains frequency information of several immune genes such as Human Leukocyte Antigens (HLA), Killer-cell Immunoglobulin-like Receptors (KIR), Major histocompatibility complex class I chain-related (MIC) genes, and a number of cytokine gene polymorphisms. The Allele Frequency Net Database (AFND) provides a central source, freely available to all, for the storage of allele frequencies from different polymorphic areas in the Human Genome. Users can contribute the results of their work into one common database and can perform database searches on information already available. We have currently collected data in allele, haplotype and genotype format. However, the success of this website will depend on you to contribute your data.
The Allen Brain Atlas provides a unique online public resource integrating extensive gene expression data, connectivity data and neuroanatomical information with powerful search and viewing tools for the adult and developing brain in mouse, human and non-human primate
ALSoD is a freely available database that has been transformed from a single gene storage facility recording mutations in the SOD1 gene to a multigene ALS bioinformatics repository and analytical instrument combining genotype, phenotype, and geographical information with associated analysis tools. These include a comparison tool to evaluate genes side by side or jointly with user configurable features, a pathogenicity prediction tool using a combination of computational approaches to distinguish variants with nonfunctional characteristics from disease-associated mutations with more dangerous consequences, and a credibility tool to enable ALS researchers to objectively assess the evidence for gene causation in ALS. Furthermore, integration of external tools, systems for feedback, annotation by users, and two-way links to collaborators hosting complementary databases further enhance the functionality of ALSoD.
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While focused on supporting the scientific community, ATCC activities range widely, from repository-related operations to providing specialized services, conducting in-house R&D and intellectual property management. ATCC serves U.S. and international researchers by characterizing cell lines, bacteria, viruses, fungi and protozoa, as well as developing and evaluating assays and techniques for validating research resources and preserving and distributing biological materials to the public and private sector research communities. Our management philosophy emphasizes customer satisfaction, value addition, cost-effective operations and competitive benchmarking for all areas of our enterprise.
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Androgen Receptor Gene Mutations Database is for all who are interested in mutations of the Androgen Receptor Gene. In light of the difficulty in getting new AR mutations published the curator will now accept new mutations that have not been published, provided that it is from a reputable research or clinical laboratory. The curator also strongly suggests that where possible, particularly in the case of new unique mutations that an attempt be made to at least confirm the pathogenicity of the putatative mutation, by showing that the mutation when transfected into a suitable expression system produces a mutant androgen receptor protein.
Genome track alignments using GBrowse on this site are featured with: (1) Annotated and predicted genes and transcripts; (2) QTL / SNP Association tracks; (3) OMIA genes; (4) Various SNP Chip tracks; (5) Other mapping fetures or elements that are available.
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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APID Interactomes is a database that provides a comprehensive collection of protein interactomes for more than 400 organisms based in the integration of known experimentally validated protein-protein physical interactions (PPIs). Construction of the interactomes is done with a methodological approach to report quality levels and coverage over the proteomes for each organism included. In this way, APID provides interactomes from specific organisms that in 25 cases have more than 500 proteins. As a whole APID includes a comprehensive compendium of 90,379 distinct proteins and 678,441 singular interactions. The analytical and integrative effort done in APID unifies PPIs from primary databases of molecular interactions (BIND, BioGRID, DIP, HPRD, IntAct, MINT) and also from experimentally resolved 3D structures (PDB) where more than two distinct proteins have been identified. In this way, 8,388 structures have been analyzed to find specific protein-protein interactions reported with details of their molecular interfaces. APID also includes a new data visualization web-tool that allows the construction of sub-interactomes using query lists of proteins of interest and the visual exploration of the corresponding networks, including an interactive selection of the properties of the interactions (i.e. the reliability of the "edges" in the network) and an interactive mapping of the functional environment of the proteins (i.e. the functional annotations of the "nodes" in the network).
ASAP (a systematic annotation package for community analysis of genomes) is a relational database and web interface developed to store, update and distribute genome sequence data and gene expression data collected by or in collaboration with researchers at the University of Wisconsin - Madison. ASAP was designed to facilitate ongoing community annotation of genomes and to grow with genome projects as they move from the preliminary data stage through post-sequencing functional analysis. The ASAP database includes multiple genome sequences at various stages of analysis, and gene expression data from preliminary experiments.
>>>>!!!!<<<< AspGD data are being integrated into FungiDB. Please click here for additional details http://fungidb.org/ . Discussion of how to maximize the value of FungiDB for the Aspergillus research community will be a major topic at the upcoming AsperFest12 meeting at Asilomar (March 16-17, 2015). >>>>!!!!<<<< AspGD is an organized collection of genetic and molecular biological information about the filamentous fungi of the genus Aspergillus. Among its many species, the genus contains an excellent model organism (A. nidulans, or its teleomorph Emericella nidulans), an important pathogen of the immunocompromised (A. fumigatus), an agriculturally important toxin producer (A. flavus), and two species used in industrial processes (A. niger and A. oryzae). AspGD contains information about genes and proteins of multiple Aspergillus species; descriptions and classifications of their biological roles, molecular functions, and subcellular localizations; gene, protein, and chromosome sequence information; tools for analysis and comparison of sequences; and links to literature information; as well as a multispecies comparative genomics browser tool (Sybil) for exploration of orthology and synteny across multiple sequenced Aspergillus species.
The Australian Drosophila Ecology and Evolution Resource (ADEER) from the Hoffmann lab and other contributors is a nationally significant life science collection. The Drosophila Clinal Data Collection contains data on populations along the eastern coast of Australia. It remains an excellent resource for understanding past and future evolutionary responses to climate change. The Drosophila Genomic Data Collection hosts Drosophila genomes sequenced as part of the Genomic Basis for Adaptation to Climate Change Project. 23 genomes have been sequenced as part of this project. Currently assemblies and annotations are available for Drosophila birchii, D. bunnanda, D. hydei, and D. repleta. The Drosophila Species Distribution Data Collection contains distribution data of nine drosophilid species that have been collected in Australia by the Hoffmann lab and other research groups between 1924 and 2005. More than 300 drosophilid species have been identified in the tropical and temperate forests located on the east coast of Australia. Many species are restricted to the tropics, a few are temperate specialists, and some have broad distributions across climatic regions. Their varied distribution along the tropical - temperate cline provide a powerful tool for studying climate adaptation and species distribution limits.
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The Autism Chromosome Rearrangement Database is a collection of hand curated breakpoints and other genomic features, related to autism, taken from publicly available literature: databases and unpublished data. The database is continuously updated with information from in-house experimental data as well as data from published research studies.
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The goal of the Autophagy Database is to provide up-to-date relevant information including protein structure data to researchers of autophagy, and to disseminate important findings to a wider audience so that their ramifications can be appreciated. For this purpose, we strive to make the database to contain as much pertinent information as possible and to make the contents freely available in a user-friendly format.
The Bacterial and Viral Bioinformatics Resource Center (BV-BRC) is an information system designed to support research on bacterial and viral infectious diseases. BV-BRC combines two long-running BRCs: PATRIC, the bacterial system, and IRD/ViPR, the viral systems.
>>>!!!Bacterial (BCSDB) and Plant&Fungal (PFCSDB) carbohydrate structure databases have been merged into a single database, CSDB!!!<<< BCSDB database is aimed at provision of structural, bibliographic, taxonomic and related information on bacterial carbohydrate structures. Two key points of this service are: covering - is above 90% in the scope of bacterial carbohydrates. This means the negative search answer remains valuable scientific information. And consistence - we manually check the data, and aim at hight quality error-free content. The main source of data is a retrospective literature analysis. About 25% of data were imported from CCSD (Carbbank, ceased in 1997, University of Georgia, Athens; structures published before 1995) with subsequent manual curation and approval. Current coverage is displayed in red on the top of the left menu. The time lag between publication of new data and their deposition ~ 1 year. The scope is "bacterial carbohydrates" and covers nearly all structures of this class published up to 2016. Bacterial means that a structure has been found in bacteria or obtained by modification of those found in bacteria. Carohydrate 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 Benchmark Energy & Geometry Database (BEGDB) collects results of highly accurate QM calculations of molecular structures, energies and properties. These data can serve as benchmarks for testing and parameterization of other computational methods.
BindingDB is a public, web-accessible knowledgebase of measured binding affinities, focusing chiefly on the interactions of proteins considered to be candidate drug-targets with ligands that are small, drug-like molecules. BindingDB supports medicinal chemistry and drug discovery via literature awareness and development of structure-activity relations (SAR and QSAR); validation of computational chemistry and molecular modeling approaches such as docking, scoring and free energy methods; chemical biology and chemical genomics; and basic studies of the physical chemistry of molecular recognition. BindingDB also includes a small collection of host-guest binding data of interest to chemists studying supramolecular systems. The data collection derives from a variety of measurement techniques, including enzyme inhibition and kinetics, isothermal titration calorimetry, NMR, and radioligand and competition assays. BindingDB includes data extracted from the literature and from US Patents by the BindingDB project, selected PubChem confirmatory BioAssays, and ChEMBL entries for which a well defined protein target ("TARGET_TYPE='PROTEIN'") is provided.
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bio.tools is a software registry for bioinformatics and the life sciences.
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor uses the R statistical programming language, and is open source and open development. It has two releases each year, and an active user community. Bioconductor is also available as an AMI (Amazon Machine Image) and a series of Docker images.
The BioCyc database collection of Pathway/Genome Databases (PGDBs) provides a reference on the genomes and metabolic pathways of thousands of sequenced organisms. BioCyc PGDBs are generated by software that predict the metabolic pathways of completely sequenced organisms, predict which genes code for missing enzymes in metabolic pathways, and predict operons. BioCyc also integrates information from other bioinformatics databases, such as protein feature and Gene Ontology information from UniProt. The BioCyc website provides a suite of software tools for database searching and visualization, for omics data analysis, and for comparative genomics and comparative pathway questions. From 2016 on, access to the EcoCyc and MetaCyc databases will remain free. Subscriptions to the other 7,600 BioCyc databases will be available to institutions (e.g., libraries), and to individuals. Access to licensed databases via: https://biocyc.org/Product-summary.shtml.