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Provides a resource for data analysis and visualization in a gene-by-gene or genome-wide scale. PlasmoDB is a functional genomic database for Plasmodium spp. It belongs to a family of genomic resources that are housed under the EuPathDB Bioinformatics Resource Center (BRC) umbrella. Data in PlasmoDB can be queried by selecting the data of interest from a query grid or drop down menus. Various results can then be combined with each other on the query history page.
BiGG Models
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Provides a library of manually-curated genome-scale metabolic models. BIGG Models compiles biochemical, genetic and genomic standardized data and supplies more than 75 models linked to genome annotations and external databases. Information can be browsed by metabolites, models or by reaction and users can compare different models. The database can also be locally downloaded by using the source code or through Docker.
CGD / Cucurbit Genomics Database
A database which offers gene annotation of cucurbit. This base offers the genome of Melon (Cucumis melo), Cucumber (Cucumis sativus), Watermelon (Citrullus lanatus), Pumpkin (Cucurbita maxima). The Cucurbitaceae consist of 98 proposed genera with 975 species, mainly in regions tropical and subtropical. All species are sensitive to frost. Most of the plants in this family are annual vines, but some are woody lianas, thorny shrubs, or trees (Dendrosicyos). Cucurbit belongs to the Cucurbitaceae family.
Gathers gene and protein information about for bacillus subtilis. SubtiWiki is a collective repository including data about more than 6000 protein and RNA-coding genes, over 1700 operons and links towards more than 6800 publications and 40 interactive maps of metabolic and regulatory pathways. The database displays records for individual gene and protein coupled to various modules dealing with metabolic pathways, regulation data, expression, manually curated protein-protein interaction data and genome.
PATRIC / Pathosystems Resource Integration Center
Aims to assist scientists in infectious-disease research. PATRIC is a National Institute of Health (NIH) supported bioinformatics resource center that has been built to enable comparative genomic analysis of bacterial pathogens. The database provides researchers with an online resource that stores and integrates a variety of data types (e.g. genomics, transcriptomics, protein-protein interactions (PPIs), three-dimensional protein structures and sequence typing data) and associated metadata. Tools and services for bacterial infectious disease research are also available.
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Offers a way to search and discover the relationships among genes, proteins, compounds and small RNAs in plant signal transduction, metabolism and gene regulatory networks. HRGRN models the interactions between nodes by defining comprehensive types of edges. It provides connection by edges between the genes with similar expression patterns, which will provide in-depth insight into gene–gene relationships. The database permits to discover novel interactions between genes and/or pathways and the built-in analysis tool available on the site allows to build subnetworks for specified nodes based on known interactions.
IRMA / In vivo “benchmarking” of Reverse-engineering and Modeling Approaches
Assesses and benchmarks modeling and reverse-engineering strategies. IRMA is a synthetic network of five genes regulating each other for in vivo reverse-engineering and modeling assessment. This database includes a variety of regulatory interactions, thus capturing the behavior of larger eukaryotic gene networks on a smaller scale. The network was designed to be negligibly affected by endogenous genes, and to respond to galactose, which triggers transcription of its genes.
An integrated database resource consisting of 16 main databases, which are categorized into systems, genomic, chemical and health information. The PATHWAY, BRITE and MODULE databases in the systems information category contain KEGG pathway maps, BRITE hierarchy and table files and KEGG modules, respectively, as representations of high-level functions. They are all manually created based on published literature. The genomic information category contains the GENOME and GENES databases for collections of organisms with complete genomes and their gene catalogs, which are mostly taken from RefSeq and GenBank databases. The COMPOUND, GLYCAN, REACTION, RPAIR, RCLASS and ENZYME databases in the chemical information category contain chemical substances and reactions and are collectively called KEGG LIGAND for historical reasons. The health information category consists of the DISEASE, DRUG, DGROUP and ENVIRON databases for disease and drug information.
Consists of a community resource dedicated to the study of parasitic nematodes. Nematode.net is a publicly available resource that provides access to annotation of genomes, expression and related genome-scale data, as well as data-mining tools and their comparative data products. NemaGene hosts annotation for almost 1.1 million genes and transcripts spanning 67 nematode species and NemaBrowse allows displaying of SnpEff-annotated variants from isolates with different phenotypes. The database is a part of Helminth.net, an evolving collection of databases hosting resources for helminths.
MGI / Mouse Genome Informatics
Provides access to integrated genetic, genomic, and biological data about the laboratory mouse to facilitate study of human health and disease. MGI is an international mouse knowledgebase that includes several topic areas: Genes; Phenotypes and Mutant Alleles; Human-Mouse: Disease Connection; Recombinase (cre); Function; Strains; Strains, Single nucleotide polymorphisms (SNPs) and Polymorphisms; Vertebrate Homology; Pathways; Batch Data and Analysis Tools; and Nomenclature. The database contains the Mouse Genome Database (MGD), the Gene Expression Database (GXD) and the Mouse Tumor Biology (MTB) Database.
AHD / Arabidopsis Hormone Database
Provides a large collection of Arabidopsis hormone related genes (AHRGs). AHD integrates detailed gene information and a phenotype ontology that is developed to precisely describe myriad hormone-regulated morphological processes with standardized vocabularies in the model organism Arabidopsis. It offers a systematic and comprehensive view of Arabidopsis hormone related genes. This database contains data on major phytohormones: abscisic acid, auxin, brassinosteroid, cytokinin, ethylene, gibberellin, jasmonic acid and salicylic acid.
ECMDB / EColi Metabolome DataBase
An expertly curated database containing extensive metabolomic data and metabolic pathway diagrams about Escherichia coli (strain K12, MG1655). This database includes significant quantities of “original” data compiled by members of the Wishart laboratory as well as additional material derived from hundreds of textbooks, scientific journals, metabolic reconstructions and other electronic databases. ECMDB currently contains 3755 small molecules with 1402 associated enzymes and 387 associated transporters. It also has 1542 metabolic pathways that are linked to 3011 metabolites. A total of 19,294 NMR and MS spectra (experimental and predicted) for 3098 different E. coli metabolites are also contained in the database. Each metabolite is linked to more than 100 data fields describing the compound, its ontology, physical properties, reactions, pathways, references, external links and associated proteins or enzymes.
Assists users to find information about crop plant metabolism. MetaCrop is an online repository that contains information at different levels of detail from overview maps to pathways, to reactions, to reaction details and contains additional related data such as literature references. It allows researchers: (1) to explore metabolic information by browsing through various levels of abstraction; (2) to integrate experimental data into metabolic pathways; and (3) to create metabolic models for simulation purposes.
Pathway Commons
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Enables biologists to browse and search a comprehensive collection of pathways from multiple sources represented in a common language, the BioPAX format. Data providers can share their pathway data via a common repository. Depending on the source database, data may include proteins, small molecules, DNA, RNA, complexes and their cellular locations, different types of physical interactions, such as molecular interaction, biochemical reaction, catalysis, complex assembly and transport, post-translational protein modifications, original citations, experimental evidence and links to other database information, such as protein sequence annotation. This database aims to collect and integrate all public pathway data available in standard formats.
A repository of genome-scale metabolic networks (GSMNs) and biochemical pathways from a number of major resources imported into a common namespace of chemical compounds, reactions, cellular compartments-namely MNXref-and proteins. MetaNetX provides a comprehensive suite of tools for the analysis of genome-scale metabolic models, based on a single integrated namespace of metabolites and metabolic reactions that integrates the most widely used biochemical databases and model repositories – MNXref. The reconciliation process used in MNXref greatly simplifies the development and analysis of genome-scale metabolic models, allowing users to concentrate on model analysis rather than the time-consuming problem of identifier mapping.
A metabolic pathway database which is able to overlay gene-to-gene and/or metabolite-to-metabolite relationships as curves on a metabolic pathway map, or on a combination of up to four maps. This representation would help to discover, for example, novel functions of a transcription factor that regulates genes on a metabolic pathway. You can upload your own data (experiment data, map data and correlation data) for analyses. Other users never allowed to access to them. After logging-off, leaving from KaPPA-View4 site, or closing the browser, all the uploaded data are to be deleted from the server.
A genomic database for Giardia lamblia. GiardiaDB is based on the genome of the WBC6 clinical isolate of G. lamblia. It is accessed via the standard EuPathDB web interface, providing a wide variety of tools for genomic database mining. In addition to BLAST and pattern/motif similarity searches, users can identify genes based on genomic position; common name or keyword; gene attributes (such as gene type, or number of exons); evidence of transcript expression including ESTs, SAGE tags, microarray and proteomics; gene product annotation (such as GO function, or EC enzyme number); and predicted cellular location (based on signal peptide and transmembrane predictions).
A catalog of known and/or predicted biochemical pathways from rice (Oryza sativa). Pathways and genes presented in this catalog are primarily based on the annotations carried out by Gramene database project on the release 5 of the TIGR-assembly of Oryza sativa japonica cv. Nipponbare genome sequenced by IRGSP. RiceCyc undergoes regular rounds of curation in order to integrate exciting new discoveries on biochemical pathways in rice. The computationally generated pathways are subjected to manual curation based on published literature.
Contains components involved in the RNA metabolic pathways of three main RNA classes (mRNA, tRNA and rRNA). RNApathwaysDB can be queried with keywords, and sequences of protein enzymes involved in RNA processing can be searched with BLAST. Options for data presentation include pathway graphs and tables with enzymes and literature data. Structures of macromolecular complexes involving RNA and proteins that act on it are presented as 'potato models' using DrawBioPath-a new javascript tool.
Omics Dashboard
Enhances the interpretation of omics data to reduce analysis time and to make omics data more accessible. Omics Dashboard is a customizable visualization tool that enables user to quickly survey cellular activity. This resource provides significance analysis (computing statistical significance and fold change), enabling the user to quickly find and understand the responses of genes within cellular subsystems of interest; gauge the relative activity levels of different cellular systems; and compare the expression levels of a cellular system with those of its known regulators.
A Pathway/Genome Database of the model eukaryote Saccharomyces cerevisiae S288c. YeastCyc contains, in addition to genomic information, metabolic pathway, reaction, enzyme, and compound information, which has been manually curated from the scientific literature. This curation process includes periodic updates to the metabolites, reactions and pathways from the current version of MetaCyc to ensure compatibility with other members of the MetaCyc family of databases. YeastCyc has been curated from 2100 publications and is part of the BioCyc database collection of 7612 microbial genomes.
RGD / Rat Genome Database
Provides a comprehensive data repository and informatics platform related to the laboratory rat, one of the most important model organisms for disease studies. Rat Genome Database (RGD) maintains and updates datasets for genomic elements such as genes, transcripts and increasingly in recent years, sequence variations, as well as map positions for multiple assemblies and sequence information. Functional annotations for genomic elements are curated from published literature, submitted by researchers and integrated from other public resources. Complementing the genomic data catalogs are those associated with phenotypes and disease, including strains, quantitative trait loci (QTL) and experimental phenotype measurements across hundreds of strains.
PMAP / Proteolysis MAP
A user-friendly website intended to aid the scientific community in reasoning about proteolytic networks and pathways. PMAP is comprised of five databases, linked together in one environment. The foundation databases, ProteaseDB and SubstrateDB, are driven by an automated annotation pipeline that generates dynamic 'Molecule Pages', rich in molecular information. PMAP also contains two community annotated databases focused on function; CutDB has information on more than 5000 proteolytic events, and ProfileDB is dedicated to information of the substrate recognition specificity of proteases. Together, the content within these four databases will ultimately feed PathwayDB, which will be comprised of known pathways whose function can be dynamically modeled in a rule-based manner, and hypothetical pathways suggested by semi-automated culling of the literature.
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