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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.

(last updated: Oct 12, 2019)

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Resource NameResource TypeDescriptionKeywordsResource IDProper CitationParent OrganizationRelated ConditionFunding AgencyRelationReferenceWebsite StatusAlternate IDsAlternate URLsOld URLs
Kidney and Urinary Pathway Knowledge BaseResource, data analysis service, production service resource, analysis service resource, data set, service resource, storage service resource, data repository, data or information resourceA collection of omics datasets (mRNA, proteins and miRNA) that have been extracted from PubMed and other related renal databases, all related to kidney physiology and pathology giving KUP biologists the means to ask queries across many resources in order to aggregate knowledge that is necessary for answering biological questions. Some microarray raw datasets have also been downloaded from the Gene Expression Omnibus and analyzed by the open-source software GeneArmada. The Semantic Web technologies, together with the background knowledge from the domain's ontologies, allows both rapid conversion and integration of this knowledge base. SPARQL endpoint The KUPKB Network Explorer will help you visualize the relationships among molecules stored in the KUPKB. A simple spreadsheet template is available for users to submit data to the KUPKB. It aims to capture a minimal amount of information about the experiment and the observations made.kidney, urinary, urine, pathway, molecule, visualizer, gene, protein, mirna, metabolite, mrna, microarray, ortholog, rdf, renal cell, anatomy, animal model, disease, sparql, proteomics, ontology, biomarker, gene expression, physiology, pathologySCR_001746(Kidney and Urinary Pathway Knowledge Base, RRID:SCR_001746)University of Manchester; Manchester; United Kingdom , National Institute of Health and Medical Research; Rennes; France Kidney diseaseEuropean Union, FP7, ICT-2007.4.4 e-LICO projectrelated to: NIDDK Information Network, Gene Expression Omnibus, Gene Ontology, KEGG, submitted by: NIDDK Information NetworkPMID:21624162Last checked downnlx_154134
Arabidopsis ReactomeResource, data or information resource, databaseCurated database of core pathways and reactions in plant biology that covers biological pathways ranging from the basic processes of metabolism to high-level processes such as cell cycle regulation. While it is targeted at Arabidopsis pathways, it also includes many biological events from other plant species. This makes the database relevant to the large number of researchers who work on other plants. Arabidopsis Reactome currently contains both in-house curated pathways as well as imported pathways from AraCyc and KEGG databases. All the curated information is backed up by its provenance: either a literature citation or an electronic inference based on sequence similarity. Their ontology ensures that the various events are linked in an appropriate spatial and temporal context.pathway, reaction, biological processSCR_002063(Arabidopsis Reactome, RRID:SCR_002063)John Innes Centre; Norwich; United Kingdom European Unionuses: AraCyc, KEGG, listed by: 3DVCLast checked downnif-0000-20812
TRANSPATHResource, data analysis service, production service resource, analysis service resource, database, service resource, data or information resourceDatabase on eukaryotic transcription factors, their experimentally-proven binding sites, consensus binding sequences (positional weight matrices) and regulated genes. Its broad compilation of binding sites allows the derivation of positional weight matrices. It can either be used as an encyclopedia, for both specific and general information on signal transduction, or can serve as a network analyzer. Cross-references to important sequence and signature databases such as EMBL/GenBank UniProt/Swiss-Prot InterPro or Ensembl EntrezGene RefSeq are provided. The database is equipped with the tools for data visualization and analysis. It has three modules: the first one is the data, which have been manually extracted, mostly from the primary literature; the second is PathwayBuilder, which provides several different types of network visualization and hence facilitates understanding; the third is ArrayAnalyzer, which is particularly suited to gene expression array interpretation, and is able to identify key molecules within signalling networks (potential drug targets). These key molecules could be responsible for the coordinated regulation of downstream events. Manual data extraction focuses on direct reactions between signalling molecules and the experimental evidence for them, including species of genes/proteins used in individual experiments, experimental systems, materials and methods. This combination of materials and methods is used in TRANSPATH to assign a quality value to each experimentally proven reaction, which reflects the probability that this reaction would happen under physiological conditions. Another important feature in TRANSPATH is the inclusion of transcription factor-gene relations, which are transferred from TRANSFAC, a database focused on transcription regulation and transcription factors. Since interactions between molecules are mainly direct, this allows a complete and stepwise pathway reconstruction from ligands to regulated genes.signal transduction, network analyzer, transcriptional regulator, transcription factor, metabolic pathway, signaling pathway, protein-protein interaction, gene-regulatory pathway, signal transduction pathway, complex, signaling molecule, reaction, molecule, gene, pathway, gene expressionSCR_005640(TRANSPATH, RRID:SCR_005640)BIOBASE Corporation BMBF, European Union, European Union FP6related to: TRANSFAC, GeneTrailReferences (4)Last checked upnif-0000-03580,,
EMBL - Bork GroupResource, laboratory portal, service resource, portal, organization portal, data or information resourceThe main focus of this Computational Biology group is to predict function and to gain insights into evolution by comparative analysis of complex molecular data. The group currently works on three different scales: * genes and proteins, * protein networks and cellular processes, and * phenotypes and environments. They require both tool development and applications. Some selected projects include comparative gene, genome and metagenome analysis, mapping interactions to proteins and pathways as well as the study of temporal and spatial protein network aspects. All are geared towards the bridging of genotype and phenotype through a better understanding of molecular and cellular processes. The services - resources & tools, developed by Bork Group, are mainly designed and maintained for research & academic purposes. Most of services are published and documented in one or more papers. All our tools can be completely customized and integrated into your existing framework. This service is provided by the company biobyte solutions GmbH. Please visit their tools and services pages for full details and more information. Standard commercial licenses for our tools are also available through biobyte solutions GmbH. The group is partially associated with Max Delbr??ck Center for Molecular Medicine (MDC), Berlin.computational biology, gene, protein, protein network, cellular process, phenotype, environment, gene, genome, metagenome, analysis, interaction, pathway, temporal, spatial, network, genotype, phenotype, molecular processSCR_000810(EMBL - Bork Group, RRID:SCR_000810)European Molecular Biology Laboratory BMBF, European Molecular Biology Laboratory, European Union, IBM, Max-Delbruck Center for Molecular MedicineLast checked upnlx_149173
InnateDBResource, data analysis service, production service resource, analysis service resource, database, service resource, data or information resourcePublicly available database of the genes, proteins, experimentally-verified interactions and signaling pathways involved in the innate immune response of humans, mice and bovines to microbial infection. The database captures coverage of the innate immunity interactome by integrating known interactions and pathways from major public databases together with manually-curated data into a centralized resource. The database can be mined as a knowledgebase or used with the integrated bioinformatics and visualization tools for the systems level analysis of the innate immune response. Although InnateDB curation focuses on innate immunity-relevant interactions and pathways, it also incorporates detailed annotation on the entire human, mouse and bovine interactomes by integrating data (178,000+ interactions & 3,900+ pathways) from several of the major public interaction and pathway databases. InnateDB also has integrated human, mouse and bovine orthology predictions generated using Ortholgue software. Ortholgue uses a phylogenetic distance-based method to identify possible paralogs in high-throughput orthology predictions. Integrated human and mouse conserved gene order and synteny information has also been determined to provide further support for orthology predictions. InnateDB Capabilities: * View statistics for manually-curated innate immunity relevant molecular interactions. New manually curated interactions are submitted weekly. * Search for genes and proteins of interest. * Search for experimentally-verified molecular interactions by gene/protein name, interaction type, cell type, etc. * Search genes/interactions belonging to 3,900 pathways. * Visualize interactions using an intuitive subcellular localization-based layout in Cerebral. * Upload your own list of genes along with associated gene expression data (from up to 10 experimental conditions) to interactively analyze this data in a molecular interaction network context. Once you have uploaded your data, you will be able to interactively visualize interaction networks with expression data overlaid; carry out Pathway, Gene Ontology and Transcription Factor Binding Site over-representation analyses; construct orthologous interaction networks in other species; and much more. * Access curated interaction data via a dedicated PSICQUIC webservice.gene, immune response, pathway, protein, signaling pathway, interaction, immune, signaling response, gene, orthology prediction, orthology, ortholg, annotation, interactome, gene expression, molecule, protein-protein interaction, molecular interaction, visualization, nucleic acid-protein, nucleic acid, network, web service, transcription factor binding site, software resourceSCR_006714(InnateDB, RRID:SCR_006714)Simon Fraser University; British Columbia; Canada , University of British Columbia; British Columbia; Canada Microbial infection, Allergy, AsthmaAllerGen, European Union, Michael Smith Foundation for Health Research, Teagascrelated to: IMEx - The International Molecular Exchange Consortium, Interaction Reference Index, ConsensusPathDB, IMEx - The International Molecular Exchange Consortium, PSICQUIC Registry, PSICQUIC, Gene Ontology, IntAct, listed by:, works_with: IMEx - The International Molecular Exchange ConsortiumReferences (2)Last checked upnif-0000-20808
G:ProfilerResource, analysis service resource, software resource, data analysis service, service resource, production service resourceA web-based toolset for functional profiling of gene lists from large-scale experiments. It has a simple web interface with powerful visualization. It currently supports 85 species, including mammals, fungi, plants, insects, etc, from the Ensembl and Ensembl Genomes databases. g:Profiler consists of the following tools: * g:GOSt retrieves most significant Gene Ontology (GO) terms, KEGG and REACTOME pathways, and TRANSFAC motifs to a user-specified group of genes, proteins or microarray probes. g:GOSt also allows analysis of ranked or ordered lists of genes, visual browsing of GO graph structure, interactive visualization of retrieved results, and many other features. Multiple testing corrections are applied to extract only statistically important results. * g:Convert allows conversion between gene or protein names, database IDs and microarray probes of more than 100 types. A mix of various IDs may be presented as input; output options include HTML, text and XLS spreadsheet. * g:Orth retrieves orthologs for a given set of genes, proteins or probes in a selected organism. Graphical representation also shows orthologs present in all g:Profiler organisms. * g:Sorter searches for similar expression profiles to a given gene, protein or probe in a large set of public microarray datasets from the Gene Expression Omnibus (GEO) database. * g:Cocoa provides a compact interface for comparing enrichments of multiple gene lists. Platform: Online toolgene, high-throughput, genomics, visualization, statistical analysis, slimmer-type tool, term enrichment, protein interaction, functional similarity, analysis, coexpression, gene id, network enrichment analysis, orthology mapping, genomic locus, ontology or annotation visualization, other analysis, ortholog, functional profile, gene list, ontology, pathway, transcription factor, microrna, regulatory motif, protein-protein interaction, biomolecule, gene expression, gene, homology, single nucleotide polymorphism, dna polymorphism, chromosome, network analysis, disease gene, rSCR_006809(G:Profiler, RRID:SCR_006809)BIIT - Bioinformatics Algorithmics and Data Mining Group EITSA, ENFIN, ERDF through EXCS funding projects, ETF7437 MEM, European Union, FP6 COBRED, University of Tartu; Tartu; Estoniarelated to: Gene Ontology, Ensembl, Ensembl Genomes, listed by: Gene Ontology Tools, OMICtoolsReferences (2)Last checked upnif-0000-31975, OMICS_02223
Malaria Parasite Metabolic PathwaysResource, data set, image collection, data or information resourceData set of metabolic pathways for the malaria parasite based on the present knowledge of parasite biochemistry and on pathways known to occur in other unicellular eukaryotes. This site extracted the pertinent information from the universal sites and presented them in an educative and informative format. The site also includes, cell-cell interactions (cytoadherence and rosetting), invasion of the erythrocyte by the parasite and transport functions. It also contains an artistic impression of the ultrastructural morphology of the interaerythrocytic cycle stages and some details about the morphology of mitochondria and the apicoplast. Most pathways are relevant to the erythrocytic phase of the parasite cycle. All maps were checked for the presence of enzyme-coding genes as they are officially annotated in the Plasmodium genome ( The site is constructed in a hierarchical pattern that permits logical deepening: * Grouped pathways of major chemical components or biological process ** Specific pathways or specific process *** Chemical structures of substrates and products or process **** Names of enzymes and their genes or components of process Each map is linked to other maps thus enabling to verify the origin of a substrate or the fate of a product. Clicking on the EC number that appears next to each enzyme, connects the site to BRENDA, SWISSPROT ExPASy ENZYME, PlasmoDB and to IUBMB reaction scheme. Clicking of the name of a metabolite, connects the site to KEGG thus providing its chemical structure and formula. Next to each enzyme there is a pie that depicts the stage-dependent transcription of the enzyme''s coding gene. The pie is constructed as a clock of the 48 hours of the parasite cycle, where red signifies over-transcription and green, under-transcription. Clicking on the pie links to the DeRisi/UCSF transcriptome database.enzyme, gene, genome, map, metabolic, mosquito, parasite, pathway, plasmodium falciparum, protein, reaction, sequence, metabolic pathway, chemical structure, cell-cell interaction, transport, morphology, mitochondria, apicoplastSCR_007072(Malaria Parasite Metabolic Pathways, RRID:SCR_007072)Hebrew University of Jerusalem; Jerusalem; Israel Malaria6th FP- BioMalPar Network of Excellence on Biology and Pathology of the Malaria Parasite, European Union, NIAID, UNDP/World Bank/WHO Special ProgrammeLast checked upnif-0000-21249
MINTResource, data or information resource, databaseA database that focuses on experimentally verified protein-protein interactions mined from the scientific literature by expert curators. The curated data can be analyzed in the context of the high throughput data and viewed graphically with the MINT Viewer. This collection of molecular interaction databases can be used to search for, analyze and graphically display molecular interaction networks and pathways from a wide variety of species. MINT is comprised of separate database components. HomoMINT, is an inferred human protein interatction database. Domino, is database of domain peptide interactions. VirusMINT explores the interactions of viral proteins with human proteins. The MINT connect viewer allows you to enter a list of proteins (e.g. proteins in a pathway) to retrieve, display and download a network with all the interactions connecting them.protein-protein interaction, protein, interaction, virus, peptide, organelle co-localization, pathway, molecular interaction, papillomavirus, epstein-barr virus, hepatitis b virus, hepatitis c virus, human adenovirus, human herpesvirus, human immunodeficiency virus, influenza a virus, vaccinia virus, simian virus 40, virus strains, virus protein, orthologous protein, network, proteomics, orthologSCR_001523(MINT, RRID:SCR_001523)University of Rome Tor Vergata; Rome; Italy AIRC Associazione Italiana per la Ricerca sul Cancro, ENFIN, European Union, HUPO Proteomics Standards Initiative, IMEx - The International Molecular Exchange Consortium, Interaction Proteome Projectrelated to: MPIDB, TissueNet - The Database of Human Tissue Protein-Protein Interactions, InteroPorc, Interaction Reference Index, Pathway Commons, ConsensusPathDB, VirusMINT, PSICQUIC Registry, Agile Protein Interactomes DataServer, uses: IntAct, PSI-MI, listed by:, affiliated with: IMEx - The International Molecular Exchange Consortium, works_with: IMEx - The International Molecular Exchange ConsortiumReferences (8)Last checked upnlx_152821
ConsensusPathDBResource, data or information resource, databaseAn integrative interaction database that integrates different types of functional interactions from heterogeneous interaction data resources. Physical protein interactions, metabolic and signaling reactions and gene regulatory interactions are integrated in a seamless functional association network that simultaneously describes multiple functional aspects of genes, proteins, complexes, metabolites, etc. With human, yeast and mouse complex functional interactions, it currently constitutes the most comprehensive publicly available interaction repository for these species. Different ways of utilizing these integrated interaction data, in particular with tools for visualization, analysis and interpretation of high-throughput expression data in the light of functional interactions and biological pathways is offered.gene regulatory network, pathway, gene regulatory network, molecular interaction, interaction, gene regulation, protein interaction, genetic interaction, biochemical reaction, drug-target interaction, molecule, visualization, gene, protein, complex, metaboliteSCR_002231(ConsensusPathDB, RRID:SCR_002231)Max Planck Institute for Molecular Genetics; Berlin; Germany European Unionrelated to: BIND, BioCarta Pathways, BioGRID, CORUM, Database of Interacting Proteins, DrugBank, HPRD - Human Protein Reference Database, HumanCyc: Encyclopedia of Homo sapiens Genes and Metabolism, Integrating Network Objects with Hierarchies, InnateDB, IntAct, KEGG, MINT, MIPS Mammalian Protein-Protein Interaction Database, MatrixDB, NetPath, Research Collaboratory for Structural Bioinformatics Protein Data Bank, PDZBase, Pathway Interaction Database, PIG - Pathogen Interaction Gateway, PINdb, PharmGKB, PhosphoPOINT, PhosphoSitePlus: Protein Modification Site, Reactome, Small Molecule Pathway Database, SignaLink, SPIKE, Therapeutic Target Database, WikiPathways, listed by: OMICtoolsReferences (4)Last checked upnif-0000-02684, OMICS_01903
BRENDAResource, data analysis service, database, analysis service resource, production service resource, service resource, storage service resource, data repository, data or information resourceMain database of functional biochemical and molecular enzyme data that provides access to seven interconnected databases. It contains 2.7 million manually annotated data on enzyme occurrence, function, kinetics and molecular properties. The majority of the data are manually extracted from the primary literature. Each entry is connected to a reference and the source organism. Enzyme ligands are stored with their structures and can be accessed via their names, synonyms or via a structure search. FRENDA (Full Reference ENzyme DAta) and AMENDA (Automatic Mining of ENzyme DAta) are based on text mining methods and represent a complete survey of PubMed abstracts with information on enzymes in different organisms, tissues or organelles. The supplemental database DRENDA provides more than 910 000 new EC number-disease relations in more than 510 000 references from automatic search and a classification of enzyme-disease-related information. KENDA (Kinetic ENzyme DAta), a new amendment extracts and displays kinetic values from PubMed abstracts. The integration of the EnzymeDetector offers an automatic comparison, evaluation and prediction of enzyme function annotations for prokaryotic genomes. The biochemical reaction database BKM-react contains non-redundant enzyme-catalyzed and spontaneous reactions and was developed to facilitate and accelerate the construction of biochemical models. The content covers information on function, structure, occurrence, preparation and application of enzymes as well as properties of mutants and engineered variants. BRENDA provides viewing options such as the display of the statistics of functional parameters and the 3D view of protein sequence and structure features. Furthermore a ligand summary shows comprehensive information on the BRENDA ligands. The enzymes are linked to their respective pathways and can be viewed in pathway maps. The disease text mining part is strongly enhanced. It is possible to submit new, not yet classified enzymes to BRENDA, which then are reviewed and classified by the International Union of Biochemistry and Molecular Biology. A new SBML output format of BRENDA kinetic data allows the construction of organism-specific metabolic models. 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. Although they intend to give a representative overview on the characteristics and variability of each enzyme the Handbook is not a compendium. The reader will have to go to the primary literature for more detailed information. Naturally it is not possible to cover all the numerous literature references for each enzyme (for some enzymes up to 40000) if the data representation is to be concise as is intended. The data collection is being developed into a metabolic network information system with links to Enzyme expression and regulation information. BRENDA SOAP Webservice is available.enzyme, metabolic pathway, protein sequence, protein structure, genome, structure, function, annotation, kinetics, molecular property, occurrence, preparation, application, mutant, variant, pathway, ligand, web service, sequence, substructureSCR_002997(BRENDA, RRID:SCR_002997)Technical University of Braunschweig; Braunschweig; Germany European Unionrelated to: ENZYMEReferences (6)Last checked upnif-0000-30222
IntActResource, service resource, data or information resource, data repository, storage service resource, databaseOpen source database system and analysis tools for molecular interaction data. All interactions are derived from literature curation or direct user submissions. Direct user submissions of molecular interaction data are encouraged, which may be deposited prior to publication in a peer-reviewed journal. The IntAct Database contains (Jun. 2014): * 447368 Interactions * 33021 experiments * 12698 publications * 82745 Interactors IntAct provides a two-tiered view of the interaction data. The search interface allows the user to iteratively develop complex queries, exploiting the detailed annotation with hierarchical controlled vocabularies. Results are provided at any stage in a simplified, tabular view. Specialized views then allows "zooming in" on the full annotation of interactions, interactors and their properties. IntAct source code and data are freely available.protein domain, motif, protein interaction, molecular interaction, interaction, protein, binary interaction, complex, data set, protein-protein interaction, pathway, small molecule-protein, nucleic acid-protein, small molecule, nucleic acid, protein binding, chromatin, cancer, apoptosis, molecular biology, virus, source code, isoform, gold standardSCR_006944(IntAct, RRID:SCR_006944)European Bioinformatics Institute European Unionrelated to: 3D-Interologs, IMEx - The International Molecular Exchange Consortium, MPIDB, TissueNet - The Database of Human Tissue Protein-Protein Interactions, InteroPorc, Interaction Reference Index, Pathway Commons, ConsensusPathDB, FlyMine, IMEx - The International Molecular Exchange Consortium, Integrated Molecular Interaction Database, VirHostNet: Virus-Host Network, PSICQUIC Registry, Universal Protein Resource, SIB Swiss Institute of Bioinformatics, I2D, InnateDB, MatrixDB, MBInfo, AgBase, Cardiovascular Gene Ontology Annotation Initiative, PSI-MI, Monarch Initiative, Agile Protein Interactomes DataServer, used by: ChannelPedia, MINT, Pathway Analysis Tool for Integration and Knowledge Acquisition, listed by: 3DVC,, OMICtools, works_with: IMEx - The International Molecular Exchange ConsortiumReferences (5)Last checked upnif-0000-03026, OMICS_01918
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