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Found 29 result(s)
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This database host for fungi data related to new classification with morphology, molecular and other important data. This fungal database allows deposition of taxonomic data, phenotypic details and other useful data, which will enhance our current taxonomic understanding and ultimately enable mycologists to gain better and updated insights into the current fungal classification system. In addition, the database will also allow access to comprehensive metadata including descriptions of voucher and type specimens.
METLIN represents the largest MS/MS collection of data with the database generated at multiple collision energies and in positive and negative ionization modes. The data is generated on multiple instrument types including SCIEX, Agilent, Bruker and Waters QTOF mass spectrometers.
caNanoLab is a data sharing portal designed to facilitate information sharing in the biomedical nanotechnology research community to expedite and validate the use of nanotechnology in biomedicine. caNanoLab provides support for the annotation of nanomaterials with characterizations resulting from physico-chemical and in vitro assays and the sharing of these characterizations and associated nanotechnology protocols in a secure fashion.
The IMEx consortium is an international collaboration between a group of major public interaction data providers who have agreed to share curation effort and develop and work to a single set of curation rules when capturing data from both directly deposited interaction data or from publications in peer-reviewed journals, capture full details of an interaction in a “deep” curation model, perform a complete curation of all protein-protein interactions experimentally demonstrated within a publication, make these interaction available in a single search interface on a common website, provide the data in standards compliant download formats, make all IMEx records freely accessible under the Creative Commons Attribution License
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.
This site offers an enormous collection of photographs of wild species and natural history objects. It covers most groups of organisms with the exception of birds and other vertebrates. The photographs are presented to illustrate biodiversity and as an aid to identification. The criterion for inclusion of a species is that it must have been, or might be expected to be, found in Britain or Ireland. BioImages follows the biological classification. This is a hierarchical system with species grouped in genera, genera in families, families in orders and so on up to kingdoms and superkingdoms. Biota takes you to the top of the classification tree.
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Morph·D·Base has been developed to serve scientific research and education. It provides a platform for storing the detailed documentation of all material, methods, procedures, and concepts applied, together with the specific parameters, values, techniques, and instruments used during morphological data production. In other words, it's purpose is to provide a publicly available resource for recording and documenting morphological metadata. Moreover, it is also a repository for different types of media files that can be uploaded in order to serve as support and empirical substantiation of the results of morphological investigations. Our long-term perspective with Morph·D·Base is to provide an instrument that will enable a highly formalized and standardized way of generating morphological descriptions using a morphological ontology that will be based on the web ontology language (OWL - http://www.w3.org/TR/owl-features/). This, however, represents a project that is still in development.
TOXNET (TOXicology Data NETwork) is a group of databases covering chemicals and drugs, diseases and the environment, environmental health, occupational safety and health, poisoning, risk assessment and regulations, and toxicology. Information in the TOXNET databases covers: Specific chemicals, mixtures, and products; Chemical nomenclature; Unknown chemicals; Special toxic effects of chemicals in humans and/or animals; Citations from the scientific literature.
The Cellular Phenotype database stores data derived from high-throughput phenotypic studies and it is being developed as part of the Systems Microscopy Network of Excellence project. The aim of the Cellular Phenotype database is to provide easy access to phenotypic data and facilitate the integration of independent phenotypic studies. Through its interface, users can search for a gene of interest, or a collection of genes, and retrieve the loss-of-function phenotypes observed, in human cells, by suppressing the expression of the selected gene(s), through RNA interference (RNAi), across independent phenotypic studies. Similarly, users can search for a phenotype of interest and retrieve the RNAi reagents that have caused such phenotype and the associated target genes. Information about specific RNAi reagents can also be obtained when searching for a reagent ID.
This library is a public and easily accessible resource database of images, videos, and animations of cells, capturing a wide diversity of organisms, cell types, and cellular processes. The purpose of this database is to advance research on cellular activity, with the ultimate goal of improving human health.
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Since the first discovery of RNA pseudoknots more and many more pseudoknots have been found. However, not all of those pseudoknot data are easy to trace. Sometimes the information is hidden in a publication where the title gives no hint that pseudoknot information is there. This was the first reason that we thought that a general accessible information source for pseudoknots would be handy.
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We developed a method, ChIP-sequencing (ChIP-seq), combining chromatin immunoprecipitation (ChIP) and massively parallel sequencing to identify mammalian DNA sequences bound by transcription factors in vivo. We used ChIP-seq to map STAT1 targets in interferon-gamma (IFN-gamma)-stimulated and unstimulated human HeLa S3 cells, and compared the method's performance to ChIP-PCR and to ChIP-chip for four chromosomes.For both Chromatin- immunoprecipation Transcription Factors and Histone modifications. Sequence files and the associated probability files are also provided.
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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.
The Database explores the interactions of chemicals and proteins. It integrates information about interactions from metabolic pathways, crystal structures, binding experiments and drug-target relationships. Inferred information from phenotypic effects, text mining and chemical structure similarity is used to predict relations between chemicals. STITCH further allows exploring the network of chemical relations, also in the context of associated binding proteins.
The Exome Aggregation Consortium (ExAC) is a coalition of investigators seeking to aggregate and harmonize exome sequencing data from a wide variety of large-scale sequencing projects, and to make summary data available for the wider scientific community. The data set provided on this website spans 60,706 unrelated individuals sequenced as part of various disease-specific and population genetic studies.
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The Swedish Human Protein Atlas project has been set up to allow for a systematic exploration of the human proteome using Antibody-Based Proteomics. This is accomplished by combining high-throughput generation of affinity-purified antibodies with protein profiling in a multitude of tissues and cells assembled in tissue microarrays. Confocal microscopy analysis using human cell lines is performed for more detailed protein localization. The program hosts the Human Protein Atlas portal with expression profiles of human proteins in tissues and cells. The main objective of the resource centre is to produce specific antibodies to human target proteins using a high-throughput production method involving the cloning and protein expression of Protein Epitope Signature Tags (PrESTs). After purification, the antibodies are used to study expression profiles in cells and tissues and for functional analysis of the corresponding proteins in a wide range of platforms.
The Database contains all publicly available HMS LINCS datasets and information for each dataset about experimental reagents (small molecule perturbagens, cells, antibodies, and proteins) and experimental and data analysis protocols.
Database of mass spectra of known, unknown and provisionally identified substances. MassBank is the first public repository of mass spectral data for sharing them among scientific research community. MassBank data are useful for the chemical identification and structure elucidation of chemical compounds detected by mass spectrometry.
The CGSC Database of E. coli genetic information includes genotypes and reference information for the strains in the CGSC collection, the names, synonyms, properties, and map position for genes, gene product information, and information on specific mutations and references to primary literature. The public version of the database includes this information and can be queried directly via this CGSC DB WebServer
CCRIS contains over 9,000 chemical records with carcinogenicity, mutagenicity, tumor promotion, and tumor inhibition test results. Data are derived from studies cited in primary journals, current awareness tools, NCI reports, and other special sources. Test results have been reviewed by experts in carcinogenesis and mutagenesis.
The EZRC at KIT houses the largest experimental fish facility in Europe with a capacity of more than 300,000 fish. Zebrafish stocks are maintained mostly as frozen sperm. Frequently requested lines are also kept alive as well as a selection of wildtype strains. Several thousand mutations in protein coding genes generated by TILLING in the Stemple lab of the Sanger Centre, Hinxton, UK and lines generated by ENU mutagenesis by the Nüsslein-Volhard lab in addition to transgenic lines and mutants generated by KIT groups or brought in through collaborations. We also accept submissions on an individual basis and ship fish upon request to PIs in Europe and elsewhere. EZRC also provides screening services and technologies such as imaging and high-throughput sequencing. Key areas include automation of embryo handling and automated image acquisition and processing. Our platform also involves the development of novel microscopy techniques (e.g. SPIM, DSLM, robotic macroscope) to permit high-resolution, real-time imaging in 4D. By association with the ComPlat platform, we can support also chemical screens and offer libraries with up to 20,000 compounds in total for external users. As another service to the community the EZRC provides plasmids (cDNAs, transgenes, Talen, Crispr/cas9) maintained by the Helmholtz repository of Bioparts (HERBI) to the scientific community. In addition the fish facility keeps a range of medaka stocks, maintained by the Loosli group.
With the creation of the Metabolomics Data Repository managed by Data Repository and Coordination Center (DRCC), the NIH acknowledges the importance of data sharing for metabolomics. Metabolomics represents the systematic study of low molecular weight molecules found in a biological sample, providing a "snapshot" of the current and actual state of the cell or organism at a specific point in time. Thus, the metabolome represents the functional activity of biological systems. As with other ‘omics’, metabolites are conserved across animals, plants and microbial species, facilitating the extrapolation of research findings in laboratory animals to humans. Common technologies for measuring the metabolome include mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR), which can measure hundreds to thousands of unique chemical entities. Data sharing in metabolomics will include primary raw data and the biological and analytical meta-data necessary to interpret these data. Through cooperation between investigators, metabolomics laboratories and data coordinating centers, these data sets should provide a rich resource for the research community to enhance preclinical, clinical and translational research.
LINCS Data Portal provides access to LINCS data from various sources. The program has six Data and Signature Generation Centers: Drug Toxicity Signature Generation Center, HMS LINCS Center, LINCS Center for Transcriptomics, LINCS Proteomic Characterization Center for Signaling and Epigenetics, MEP LINCS Center, and NeuroLINCS Center.
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Stemformatics is a collaboration between the stem cell and bioinformatics community. We were motivated by the plethora of exciting cell models in the public and private domains, and the realisation that for many biologists these were mostly inaccessible. We wanted a fast way to find and visualise interesting genes in these exemplar stem cell datasets. We'd like you to explore. You'll find data from leading stem cell laboratories in a format that is easy to search, easy to visualise and easy to export.