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Found 120 result(s)
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).
>>>>!!!!<<<< 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 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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BaAMPs is the first database dedicated to antimicrobial peptides (AMPs) specifically tested against microbial biofilms. The aim of this project is to provide useful resources for the study of AMPs against biofilms to microbiologist, bioinformatics researcher and medical scientist working in this field in an open-access framework.
The Biological General Repository for Interaction Datasets (BioGRID) is a public database that archives and disseminates genetic and protein interaction data from model organisms and humans. BioGRID is an online interaction repository with data compiled through comprehensive curation efforts. All interaction data are freely provided through our search index and available via download in a wide variety of standardized formats.
The BioImage Archive stores and distributes life sciences imaging datasets. It supports deposition of biological imaging data associated with publications for the whole research community, as well as reference imaging datasets. All data deposited to the BioImage Archive is made openly accessible to the scientific community.
BioModels is a repository of mathematical models of biological and biomedical systems. It hosts a vast selection of existing literature-based physiologically and pharmaceutically relevant mechanistic models in standard formats. Our mission is to provide the systems modelling community with reproducible, high-quality, freely-accessible models published in the scientific literature.
The BioProject database is a searcheable collection of complete and incomplete (in-progress) large-scale molecular projects including genome sequencing and assembly, transcriptome, metagenomic, annotation, expression and mapping projects. BioProject provides a central point to link to all data associated with a project in the NCBI molecular and literature databases.
The BioStudies database holds descriptions of biological studies, links to data from these studies in other databases at EMBL-EBI or outside, as well as data that do not fit in the structured archives at EMBL-EBI. The database accepts submissions via an online tool, or in a simple tab-delimited format. It also enables authors to submit supplementary information and link to it from the publication.
The Brain Transcriptome Database (BrainTx) project aims to create an integrated platform to visualize and analyze our original transcriptome data and publicly accessible transcriptome data related to the genetics that underlie the development, function, and dysfunction stages and states of the brain.
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.
Candida Genome Database, a resource for genomic sequence data and gene and protein information for Candida albicans and related species. CGD is based on the Saccharomyces Genome Database. The Candida Genome Database (CGD) provides online access to genomic sequence data and manually curated functional information about genes and proteins of the human pathogen Candida albicans and related species. C. albicans is the best studied of the human fungal pathogens. It is a common commensal organism of healthy individuals, but can cause debilitating mucosal infections and life-threatening systemic infections, especially in immunocompromised patients. C. albicans also serves as a model organism for the study of other fungal pathogens.
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.
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The Chickpea Transcriptome Database (CTDB) has been developed with the view to provide most comprehensive information about the chickpea transcriptome, the most relevant part of the genome. The database contains various information and tools for transcriptome sequence, functional annotation, conserved domain(s), transcription factor families, molecular markers (microsatellites and single nucleotide polymorphisms), Comprehensive gene expression and comparative genomics with other legumes. The database is a freely available resource, which provides user scientists/breeders a portal to search, browse and query the data to facilitate functional and applied genomics research in chickpea and other legumes. The current release of database provides transcriptome sequence from cultivated (Cicer arietinum desi (ICC4958) and kabuli (ICCV2)) and wild (Cicer reticulatum, PI489777) chickpea genotypes.
Complete Genomics provides free public access to a variety of whole human genome data sets generated from Complete Genomics’ sequencing service. The research community can explore and familiarize themselves with the quality of these data sets, review the data formats provided from our sequencing service, and augment their own research with additional summaries of genomic variation across a panel of diverse individuals. The quality of these data sets is representative of what a customer can expect to receive for their own samples. This public genome repository comprises genome results from both our Standard Sequencing Service (69 standard, non-diseased samples) and the Cancer Sequencing Service (two matched tumor and normal sample pairs). In March 2013 Complete Genomics was acquired by BGI-Shenzhen , the world’s largest genomics services company. BGI is a company headquartered in Shenzhen, China that provides comprehensive sequencing and bioinformatics services for commercial science, medical, agricultural and environmental applications. Complete Genomics is now focused on building a new generation of high-throughput sequencing technology and developing new and exciting research, clinical and consumer applications.
The Complex Portal is a manually curated, encyclopaedic resource of macromolecular complexes from a number of key model organisms, entered into the IntAct molecular interaction database (https://www.ebi.ac.uk/intact/). Data includes protein-only complexes as well as protein-small molecule and protein-nucleic acid complexes. All complexes are derived from physical molecular interaction evidences extracted from the literature and cross-referenced in the entry, or by curator inference from information on homologs in closely related species or by inference from scientific background. All complexes are tagged with Evidence and Conclusion Ontology codes to indicate the type of evidence available for each entry.
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ConsensusPathDB integrates interaction networks in humans (and in the model organisms - yeast and mouse) including binary and complex protein-protein, genetic, metabolic, signaling, gene regulatory and drug-target interactions, as well as biochemical pathways. Data originate from public resources for interactions and interactions curated from the literature. The interaction data are integrated in a complementary manner to avoid redundancies.
The Coronavirus Antiviral Research Database is designed to expedite the development of SARS-CoV-2 antiviral therapy. It will benefit global coronavirus drug development efforts by (1) promoting uniform reporting of experimental results to facilitate comparisons between different candidate antiviral compounds; (2) identifying gaps in coronavirus antiviral drug development research; (3) helping scientists, clinical investigators, public health officials, and funding agencies prioritize the most promising compounds and repurposed drugs for further development; (4) providing an objective, evidenced-based, source of information for the public; and (5) creating a hub for the exchange of ideas among coronavirus researchers whose feedback is sought and welcomed. By comprehensively reviewing all published laboratory, animal model, and clinical data on potential coronavirus therapies, the Database makes it unlikely that promising treatment approaches will be overlooked. In addition, by making it possible to compare the underlying data associated with competing treatment strategies, stakeholders will be better positioned to prioritize the most promising anti-coronavirus compounds for further development.
<<<!!!<<< Phasing out support for the Database of Genomic Variants archive (DGVa). The submission, archiving, and presentation of structural variation services offered by the DGVa is transitioning to the European Variation Archive (EVA) https://www.re3data.org/repository/r3d100011553. All of the data shown in the DGVa website is already searchable and browsable from the EVA Study Browser. Submission of structural variation data to EVA is done using the VCF format. The VCF specification allows representing multiple types of structural variants such as insertions, deletions, duplications and copy-number variants. Other features such as symbolic alleles, breakends, confidence intervals etc., support more complex events, such as translocations at an imprecise position. >>>!!!>>>
DEPOD - the human DEPhOsphorylation Database (version 1.1) is a manually curated database collecting human active phosphatases, their experimentally verified protein and non-protein substrates and dephosphorylation site information, and pathways in which they are involved. It also provides links to popular kinase databases and protein-protein interaction databases for these phosphatases and substrates. DEPOD aims to be a valuable resource for studying human phosphatases and their substrate specificities and molecular mechanisms; phosphatase-targeted drug discovery and development; connecting phosphatases with kinases through their common substrates; completing the human phosphorylation/dephosphorylation network.