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Found 126 result(s)
virus mentha archives evidence about viral interactions collected from different sources and presents these data in a complete and comprehensive way. Its data comes from manually curated protein-protein interaction databases that have adhered to the IMEx consortium. virus mentha is a resource that offers a series of tools to analyse selected proteins in the context of a network of interactions. Protein interaction databases archive protein-protein interaction (PPI) information from published articles. However, no database alone has sufficient literature coverage to offer a complete resource to investigate "the interactome". virus mentha's approach generates every week a consistent interactome (graph). Most importantly, the procedure assigns to each interaction a reliability score that takes into account all the supporting evidence. virus mentha offers direct access to viral families such as: Orthomyxoviridae, Orthoretrovirinae and Herpesviridae plus, it offers the unique possibility of searching by host organism. The website and the graphical application are designed to make the data stored in virus mentha accessible and analysable to all users.virus mentha superseeds VirusMINT. The Source databases are: MINT, DIP, IntAct, MatrixDB, BioGRID.
The NDEx Project provides an open-source framework where scientists and organizations can share, store, manipulate, and publish biological network knowledge. The NDEx Project maintains a free, public website; alternatively, users can also decide to run their own copies of the NDEx Server software in cases where the stored networks must be kept in a highly secure environment (such as for HIPAA compliance) or where high application load is incompatible with a shared public resource.
<<<!!!<<< The page is no longer available. This database was already retired, and on this page users could find information on how to search and use these sequences. dbSTS was an NCBI resource that contained sequence data for short genomic landmark sequences or Sequence Tagged Sites. STS sequences are incorporated into the STS Division of GenBank. >>>!!!>>>
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>>>!!!<<<As stated 2017-05-23 Cancer GEnome Mine is no longer available >>>!!!<<< Cancer GEnome Mine is a public database for storing clinical information about tumor samples and microarray data, with emphasis on array comparative genomic hybridization (aCGH) and data mining of gene copy number changes.
The miRBase database is a searchable database of published miRNA sequences and annotation. Each entry in the miRBase Sequence database represents a predicted hairpin portion of a miRNA transcript (termed mir in the database), with information on the location and sequence of the mature miRNA sequence (termed miR). Both hairpin and mature sequences are available for searching and browsing, and entries can also be retrieved by name, keyword, references and annotation. All sequence and annotation data are also available for download. The miRBase Registry provides miRNA gene hunters with unique names for novel miRNA genes prior to publication of results.
>>>!!!<<< caArray Retirement Announcement >>>!!!<<< The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) instance of the caArray database was retired on March 31st, 2015. All publicly-accessible caArray data and annotations will be archived and will remain available via FTP download https://wiki.nci.nih.gov/x/UYHeDQ and is also available at GEO http://www.ncbi.nlm.nih.gov/geo/ . >>>!!!<<< While NCI will not be able to provide technical support for the caArray software after the retirement, the source code is available on GitHub https://github.com/NCIP/caarray , and we encourage continued community development. Molecular Analysis of Brain Neoplasia (Rembrandt fine-00037) gene expression data has been loaded into ArrayExpress: http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-3073 >>>!!!<<< caArray is an open-source, web and programmatically accessible microarray data management system that supports the annotation of microarray data using MAGE-TAB and web-based forms. Data and annotations may be kept private to the owner, shared with user-defined collaboration groups, or made public. The NCI instance of caArray hosts many cancer-related public datasets available for download.
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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).
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.
GeneLab is an interactive, open-access resource where scientists can upload, download, store, search, share, transfer, and analyze omics data from spaceflight and corresponding analogue experiments. Users can explore GeneLab datasets in the Data Repository, analyze data using the Analysis Platform, and create collaborative projects using the Collaborative Workspace. GeneLab promises to facilitate and improve information sharing, foster innovation, and increase the pace of scientific discovery from extremely rare and valuable space biology experiments. Discoveries made using GeneLab have begun and will continue to deepen our understanding of biology, advance the field of genomics, and help to discover cures for diseases, create better diagnostic tools, and ultimately allow astronauts to better withstand the rigors of long-duration spaceflight. GeneLab helps scientists understand how the fundamental building blocks of life itself – DNA, RNA, proteins, and metabolites – change from exposure to microgravity, radiation, and other aspects of the space environment. GeneLab does so by providing fully coordinated epigenomics, genomics, transcriptomics, proteomics, and metabolomics data alongside essential metadata describing each spaceflight and space-relevant experiment. By carefully curating and implementing best practices for data standards, users can combine individual GeneLab datasets to gain new, comprehensive insights about the effects of spaceflight on biology. In this way, GeneLab extends the scientific knowledge gained from each biological experiment conducted in space, allowing scientists from around the world to make novel discoveries and develop new hypotheses from these priceless data.
The PhenoGen website shares experimental data with a worldwide community of investigators and provides a flexible, integrated, multi-resolution repository of neuroscience transcriptomic genetic data for collaborative research on genomic disorders. The main development focus is on providing Hybrid Rat Diversity Panel transcriptomic data (sequencing, genome coverage, reconstructed totalRNA/smallRNA transcriptomes, quanification of the transcriptome, eQTLs, and WGCNA) and integrating additional tools to provide platform for visualization and analysis of HRDP transcriptome data.
I2D (Interologous Interaction Database) is an on-line database of known and predicted mammalian and eukaryotic protein-protein interactions. It has been built by mapping high-throughput (HTP) data between species. Thus, until experimentally verified, these interactions should be considered "predictions". It remains one of the most comprehensive sources of known and predicted eukaryotic PPI. I2D includes data for S. cerevisiae, C. elegans, D. melonogaster, R. norvegicus, M. musculus, and H. sapiens.
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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ALEXA is a microarray design platform for 'alternative expression analysis'. This platform facilitates the design of expression arrays for analysis of mRNA isoforms generated from a single locus by the use of alternative transcription initiation, splicing and polyadenylation sites. We use the term 'ALEXA' to describe a collection of novel genomic methods for 'alternative expression' analysis. 'Alternative expression' refers to the identification and quantification of alternative mRNA transcripts produced by alternative transcript initiation, alternative splicing and alternative polyadenylation. This website provides supplementary materials, source code and other downloads for recent publications describing our studies of alternative expression (AE). Most recently we have developed a method, 'ALEXA-Seq' and associated resources for alternative expression analysis by massively parallel RNA sequencing.
MalaCards is an integrated database of human maladies and their annotations, modeled on the architecture and richness of the popular GeneCards database of human genes. MalaCards mines and merges varied web data sources to generate a computerized web card for each human disease. Each MalaCard contains disease specific prioritized annotative information, as well as links between associated diseases, leveraging the GeneCards relational database, search engine, and GeneDecks set-distillation tool. As proofs of concept of the search/distill/infer pipeline we find expected elucidations, as well as potentially novel ones.
InterPro collects information about protein sequence analysis and classification, providing access to a database of predictive protein signatures used for the classification and automatic annotation of proteins and genomes. Sequences in InterPro are classified at superfamily, family, and subfamily. InterPro predicts the occurrence of functional domains, repeats, and important sites, and adds in-depth annotation such as GO terms to the protein signatures.
The Yeast Resource Center provides access to data about mass spectrometry, yeast two-hybrid arrays, deconvolution florescence microscopy, protein structure prediction and computational biology. These services are provided to further the goal of a complete understanding of the chemical interactions required for the maintenance and faithful reproduction of a living cell. The observation that the fundamental biological processes of yeast are conserved among all eukaryotes ensures that this knowledge will shape and advance our understanding of living systems.
The Ensembl genome annotation system, developed jointly by the EBI and the Wellcome Trust Sanger Institute, has been used for the annotation, analysis and display of vertebrate genomes since 2000. Since 2009, the Ensembl site has been complemented by the creation of five new sites, for bacteria, protists, fungi, plants and invertebrate metazoa, enabling users to use a single collection of (interactive and programatic) interfaces for accessing and comparing genome-scale data from species of scientific interest from across the taxonomy. In each domain, we aim to bring the integrative power of Ensembl tools for comparative analysis, data mining and visualisation across genomes of scientific interest, working in collaboration with scientific communities to improve and deepen genome annotation and interpretation.
The UniProt Reference Clusters (UniRef) provide clustered sets of sequences from the UniProt Knowledgebase (including isoforms) and selected UniParc records in order to obtain complete coverage of the sequence space at several resolutions while hiding redundant sequences (but not their descriptions) from view.