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Found 19 result(s)
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Pathway Commons is a convenient point of access to biological pathway information collected from public pathway databases. Information is sourced from public pathway databases and is readily searched, visualized, and downloaded. The data is freely available under the license terms of each contributing database.
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WikiPathways was established to facilitate the contribution and maintenance of pathway information by the biology community. WikiPathways is an open, collaborative platform dedicated to the curation of biological pathways. WikiPathways thus presents a new model for pathway databases that enhances and complements ongoing efforts, such as KEGG, Reactome and Pathway Commons. Building on the same MediaWiki software that powers Wikipedia, we added a custom graphical pathway editing tool and integrated databases covering major gene, protein, and small-molecule systems. The familiar web-based format of WikiPathways greatly reduces the barrier to participate in pathway curation. More importantly, the open, public approach of WikiPathways allows for broader participation by the entire community, ranging from students to senior experts in each field. This approach also shifts the bulk of peer review, editorial curation, and maintenance to the community.
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Reactome is a manually curated, peer-reviewed pathway database, annotated by expert biologists and cross-referenced to bioinformatics databases. Its aim is to share information in the visual representations of biological pathways in a computationally accessible format. Pathway annotations are authored by expert biologists, in collaboration with Reactome editorial staff and cross-referenced to many bioinformatics databases. These include NCBI Gene, Ensembl and UniProt databases, the UCSC and HapMap Genome Browsers, the KEGG Compound and ChEBI small molecule databases, PubMed, and Gene Ontology.
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<<<!!!<<< This repository is no longer available. >>>!!!>>>
NetPath is currently one of the largest open-source repository of human signaling pathways that is all set to become a community standard to meet the challenges in functional genomics and systems biology. Signaling networks are the key to deciphering many of the complex networks that govern the machinery inside the cell. Several signaling molecules play an important role in disease processes that are a direct result of their altered functioning and are now recognized as potential therapeutic targets. Understanding how to restore the proper functioning of these pathways that have become deregulated in disease, is needed for accelerating biomedical research. This resource is aimed at demystifying the biological pathways and highlights the key relationships and connections between them. Apart from this, pathways provide a way of reducing the dimensionality of high throughput data, by grouping thousands of genes, proteins and metabolites at functional level into just several hundreds of pathways for an experiment. Identifying the active pathways that differ between two conditions can have more explanatory power than just a simple list of differentially expressed genes and proteins.
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PathCards is an integrated database of human biological pathways and their annotations. Human pathways were clustered into SuperPaths based on gene content similarity. Each PathCard provides information on one SuperPath which represents one or more human pathways.
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MetaCyc is a curated database of experimentally elucidated metabolic pathways from all domains of life.
MetaCyc contains pathways involved in both primary and secondary metabolism, as well as associated metabolites, reactions, enzymes, and genes. The goal of MetaCyc is to catalog the universe of metabolism by storing a representative sample of each experimentally elucidated pathway.
MetaCyc applications include: Online encyclopedia of metabolism, Prediction of metabolic pathways in sequenced genomes, Support metabolic engineering via enzyme database, Metabolite database aids. metabolomics research.
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<<<!!!<<< The NCBI BioSystems Database will be retired in March 2022. >>>!!!>>>
This retirement includes the representation of BioSystems records in the NCBI Entrez system and viewers of BioSystems content.
NCBI now provides metabolic pathway and other biosystems data through the regularly updated PubChem Pathways resource (https://pubchemdocs.ncbi.nlm.nih.gov/pathways) that offers a fresh, extended, and more modern interface.
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BiGG is a knowledgebase of Biochemically, Genetically and Genomically structured genome-scale metabolic network reconstructions. BiGG integrates several published genome-scale metabolic networks into one resource with standard nomenclature which allows components to be compared across different organisms. BiGG can be used to browse model content, visualize metabolic pathway maps, and export SBML files of the models for further analysis by external software packages. Users may follow links from BiGG to several external databases to obtain additional information on genes, proteins, reactions, metabolites and citations of interest.
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MetaboLights is a database for Metabolomics experiments and derived information. The database is cross-species, cross-technique and covers metabolite structures and their reference spectra as well as their biological roles, locations and concentrations, and experimental data from metabolic experiments.
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>>>!!!<<< Noticed 26.08.2020: The NCI CBIIT instance of the CGAP no longer exist on this website. The Mitelman Database of Chromosome Aberrations and Gene Fusions in Cancer has a new home at the NCI-funded Institute for Systems Biology Cancer Genomics Cloud available at the following location: https://mitelmandatabase.isb-cgc.org >>>!!!<<<
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GeneCards is a searchable, integrative database that provides comprehensive, user-friendly information on all annotated and predicted human genes. It automatically integrates gene-centric data from ~125 web sources, including genomic, transcriptomic, proteomic, genetic, clinical and functional information.
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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.
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<<<!!!<<< DTU Bioinformatics was closed on 31 December 2018 as part of a reorganization at DTU >>>!!!>>>
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KEGG is a database resource for understanding high-level functions and utilities of the biological system, such as the cell, the organism and the ecosystem, from molecular-level information, especially large-scale molecular datasets generated by genome sequencing and other high-throughput experimental technologies
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The Saccharomyces Genome Database (SGD) provides comprehensive integrated biological information for the budding yeast Saccharomyces cerevisiae along with search and analysis tools to explore these data, enabling the discovery of functional relationships between sequence and gene products in fungi and higher organisms.
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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
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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.
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Rhea is a freely available and comprehensive resource of expert-curated biochemical reactions. It has been designed to provide a non-redundant set of chemical transformations for applications such as the functional annotation of enzymes, pathway inference and metabolic network reconstruction. There are three types of reaction participants (reactants and products): Small molecules, Rhea polymers, Generic compounds.
All three types of reaction participants are linked to the ChEBI database (Chemical Entities of Biological Interest) which provides detailed information about structure, formula and charge. Rhea provides built-in validations that ensure both mass and charge balance of the reactions. We have populated the database with the reactions found in the enzyme classification (i.e. in the IntEnz and ENZYME databases), extending it with additional known reactions of biological interest. While the main focus of Rhea is enzyme-catalysed reactions, other biochemical reactions (including those that are often termed "spontaneous") also are included.
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The DrugBank database is a unique bioinformatics and cheminformatics resource that combines detailed drug (i.e. chemical, pharmacological and pharmaceutical) data with comprehensive drug target (i.e. sequence, structure, and pathway) information. The latest release of DrugBank (version 5.1.1, released 2018-07-03) contains 11,881 drug entries including 2,526 approved small molecule drugs, 1,184 approved biotech (protein/peptide) drugs, 129 nutraceuticals and over 5,751 experimental drugs. Additionally, 5,132 non-redundant protein (i.e. drug target/enzyme/transporter/carrier) sequences are linked to these drug entries. Each DrugCard entry contains more than 200 data fields with half of the information being devoted to drug/chemical data and the other half devoted to drug target or protein data.
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Tthe Lipidomics Gateway - a free, comprehensive website for researchers interested in lipid biology, provided by the LIPID MAPS (Lipid Metabolites and Pathways Strategy) Consortium. The LIPID MAPS Lipidomics Gateway provides a rich collection of information and resources to help you stay abreast of the latest developments in this rapidly expanding field. LIPID Metabolites And Pathways Strategy (LIPID MAPS®) is a multi-institutional effort created in 2003 to identify and quantitate, using a systems biology approach and sophisticated mass spectrometers, all of the major — and many minor — lipid species in mammalian cells, as well as to quantitate the changes in these species in response to perturbation.
The ultimate goal of our research is to better understand lipid metabolism and the active role lipids play in diabetes, stroke, cancer, arthritis, Alzheimer's and other lipid-based diseases in order to facilitate development of more effective treatments.
Since our inception, we have made great strides toward defining the "lipidome" (an inventory of the thousands of individual lipid molecular species) in the mouse macrophage. We have also worked to make lipid analysis easier and more accessible for the broader scientific community and to advance a robust research infrastructure for the international research community. We share new lipidomics findings and methods, hold annual meetings open to all interested investigators, and are exploring joint efforts to extend the use of these powerful new methods to new applications
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- Cite this service: re3data.org - Registry of Research Data Repositories. https://doi.org/10.17616/R3D last accessed: 2024-04-25
