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Found 48 result(s)
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The goal of the Autophagy Database is to provide up-to-date relevant information including protein structure data to researchers of autophagy, and to disseminate important findings to a wider audience so that their ramifications can be appreciated. For this purpose, we strive to make the database to contain as much pertinent information as possible and to make the contents freely available in a user-friendly format.
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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).
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<<<!!!<<< This repository is no longer available. >>>!!!>>> A human interactome map. The sequencing of the human genome has provided a surprisingly small number of genes, indicating that the complex organization of life is not reflected in the gene number but, rather, in the gene products – that is, in the proteins. These macromolecules regulate the vast majority of cellular processes by their ability to communicate with each other and to assemble into larger functional units. Therefore, the systematic analysis of protein-protein interactions is fundamental for the understanding of protein function, cellular processes and, ultimately, the complexity of life. Moreover, interactome maps are particularly needed to link new proteins to disease pathways and the identification of novel drug targets.
IMGT/mAb-DB provides a unique expertised resource on monoclonal antibodies (mAbs) with diagnostic or therapeutic indications, fusion proteins for immune applications (FPIA), composite proteins for clinical applications (CPCA) and relative proteins of the immune system (RPI) with clinical indications.
The UniPROBE (Universal PBM Resource for Oligonucleotide Binding Evaluation) database hosts data generated by universal protein binding microarray (PBM) technology on the in vitro DNA binding specificities of proteins. This initial release of the UniPROBE database provides a centralized resource for accessing comprehensive data on the preferences of proteins for all possible sequence variants ('words') of length k ('k-mers'), as well as position weight matrix (PWM) and graphical sequence logo representations of the k-mer data. In total, the database currently hosts DNA binding data for 406 nonredundant proteins from a diverse collection of organisms, including the prokaryote Vibrio harveyi, the eukaryotic malarial parasite Plasmodium falciparum, the parasitic Apicomplexan Cryptosporidium parvum, the yeast Saccharomyces cerevisiae, the worm Caenorhabditis elegans, mouse, and human. The database's web tools (on the right) include a text-based search, a function for assessing motif similarity between user-entered data and database PWMs, and a function for locating putative binding sites along user-entered nucleotide sequences
This Web resource provides data and information relevant to SARS coronavirus. It includes links to the most recent sequence data and publications, to other SARS related resources, and a pre-computed alignment of genome sequences from various isolates. The genome of SARS-CoV consists of a single, positive-strand RNA that is approximately 29,700 nucleotides long. The overall genome organization of SARS-CoV is similar to that of other coronaviruses. The reference genome includes 13 genes, which encode at least 14 proteins. Two large overlapping reading frames (ORFs) encompass 71% of the genome. The remainder has 12 potential ORFs, including genes for structural proteins S (spike), E (small envelope), M (membrane), and N (nucleocapsid). Other potential ORFs code for unique putative SARS-CoV-specific polypeptides that lack obvious sequence similarity to known proteins.
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During cell cycle, numerous proteins temporally and spatially localized in distinct sub-cellular regions including centrosome (spindle pole in budding yeast), kinetochore/centromere, cleavage furrow/midbody (related or homolog structures in plants and budding yeast called as phragmoplast and bud neck, respectively), telomere and spindle spatially and temporally. These sub-cellular regions play important roles in various biological processes. In this work, we have collected all proteins identified to be localized on kinetochore, centrosome, midbody, telomere and spindle from two fungi (S. cerevisiae and S. pombe) and five animals, including C. elegans, D. melanogaster, X. laevis, M. musculus and H. sapiens based on the rationale of "Seeing is believing" (Bloom K et al., 2005). Through ortholog searches, the proteins potentially localized at these sub-cellular regions were detected in 144 eukaryotes. Then the integrated and searchable database MiCroKiTS - Midbody, Centrosome, Kinetochore, Telomere and Spindle has been established.
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The Global Proteome Machine (GPM) is a protein identification database. This data repository allows users to post and compare results. GPM's data is provided by contributors like The Informatics Factory, University of Michigan, and Pacific Northwestern National Laboratories. The GPM searchable databases are: GPMDB, pSYT, SNAP, MRM, PEPTIDE and HOT.
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A small genotype data repository containing data used in recent papers from the Estonian Biocentre. Most of the data pertains to human population genetics. PDF files of the papers are also freely available.
Chemical Entities of Biological Interest (ChEBI) is a freely available dictionary of 'small molecular entities'. The term 'molecular entity' encompasses any constitutionally or isotopically distinct atom, molecule, ion, ion pair, radical, radical ion, complex, conformer, etc., identifiable as a separately distinguishable entity. The molecular entities in question are either products of nature or synthetic products used to intervene in the processes of living organisms (either deliberately, as for drugs, or unintentionally', as for chemicals in the environment). The qualifier 'small' implies the exclusion of entities directly encoded by the genome, and thus as a rule nucleic acids, proteins and peptides derived from proteins by cleavage are not included.
OrthoMCL is a genome-scale algorithm for grouping orthologous protein sequences. It provides not only groups shared by two or more species/genomes, but also groups representing species-specific gene expansion families. So it serves as an important utility for automated eukaryotic genome annotation. OrthoMCL starts with reciprocal best hits within each genome as potential in-paralog/recent paralog pairs and reciprocal best hits across any two genomes as potential ortholog pairs. Related proteins are interlinked in a similarity graph. Then MCL (Markov Clustering algorithm,Van Dongen 2000; www.micans.org/mcl) is invoked to split mega-clusters. This process is analogous to the manual review in COG construction. MCL clustering is based on weights between each pair of proteins, so to correct for differences in evolutionary distance the weights are normalized before running MCL.
>>>!!!<<< as stated 2017-06-09 MPIDB is no longer available under URL http://www.jcvi.org/mpidb/about.php >>>!!!<<< The microbial protein interaction database (MPIDB) aims to collect and provide all known physical microbial interactions. Currently, 24,295 experimentally determined interactions among proteins of 250 bacterial species/strains can be browsed and downloaded. These microbial interactions have been manually curated from the literature or imported from other databases (IntAct, DIP, BIND, MINT) and are linked to 26,578 experimental evidences (PubMed ID, PSI-MI methods). In contrast to these databases, interactions in MPIDB are further supported by 68,346 additional evidences based on interaction conservation, protein complex membership, and 3D domain contacts (iPfam, 3did). We do not include (spoke/matrix) binary interactions infered from pull-down experiments.
The Ligand-Gated Ion Channel database provides access to information about transmembrane proteins that exist under different conformations, with three primary subfamilies: the cys-loop superfamily, the ATP gated channels superfamily, and the glutamate activated cationic channels superfamily. The development of the Ligand-Gated Ion Channel database was started in 1994, as part of Le Novère's work on the phylogeny of those receptors' subunits. It grew into a serious data resource, that served the community at large. However, it is not actively maintained anymore. In addition, bioinformatics technology evolved a lot over the last two decades, so that scientists can now generate quickly customised databases from trustworthy primary data resources. Therefore, we decided to officialy freeze the data resource. The resource will not disappear, and all the information and links will stay there. But people should not consider it as an up-to-date trustable resource. For any new work, they should consider using alternative sources, such as UniProt, Ensembl, Protein Databank etc.
The PeptideAtlas validates expressed proteins to provide eukaryotic genome data. Peptide Atlas provides data to advance biological discoveries in humans. The PeptideAtlas accepts proteomic data from high-throughput processes and encourages data submission.
mentha archives evidence 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. The aggregated data forms an interactome which includes many organisms. 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". 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. mentha offers eight interactomes (Homo sapiens, Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Escherichia coli K12, Mus musculus, Rattus norvegicus, Saccharomyces cerevisiae) plus a global network that comprises every organism, including those not mentioned. The website and the graphical application are designed to make the data stored in mentha accessible and analysable to all users. Source databases are: MINT, IntAct, DIP, MatrixDB and BioGRID.
SWATHAtlas is a repository of mass spectrometry data of the human proteome. The repository provides open access to libraries of SWATH-MS (Sequential Windowed Acquisition of All Theoretical Fragment Ion Mass Spectra) datasets. SWATH-MS is a method which combines both data-independent acquisition (DIA) and targeted data analysis techniques for the collection and storage of fragmentation spectra of peptides. Compared to techniques of selected reaction monitoring (SRM), SWATH-MS allows for a more extensive throughput of proteins in a sample to be targeted. The spectra collected in SWATHAtlas can be interpreted with the help of software such as OpenSWATH or Peakview.
Swiss Institute of Bioinformatics (SIB) coordinates research and education in bioinformatics throughout Switzerland and provides bioinformatics services to the national and international research community. ExPASy gives access to numerous repositories and databases of SIB. For example: array map, MetaNetX, SWISS-MODEL and World-2DPAGE, and many others see a list here http://www.expasy.org/resources
<<<!!!<<< Effective May 2024, NCBI's Assembly resource will no longer be available. NCBI Assembly data can now be found on the NCBI Datasets genome pages. https://www.re3data.org/repository/r3d100014298 >>>!!!>>> A database providing information on the structure of assembled genomes, assembly names and other meta-data, statistical reports, and links to genomic sequence data.
The HomoloGene database provides a system for the automated detection of homologs among annotated genes of genomes across multiple species. These homologs are fully documented and organized by homology group. HomoloGene processing uses proteins from input organisms to compare and sequence homologs, mapping back to corresponding DNA sequences.
The Restriction Enzyme Database is a collection of information about restriction enzymes, methylases, the microorganisms from which they have been isolated, recognition sequences, cleavage sites, methylation specificity, the commercial availability of the enzymes, and references - both published and unpublished observations (dating back to 1952). REBASE is updated daily and is constantly expanding.
The NIH 3D Print Exchange (the “Exchange”) is an open, comprehensive, and interactive website for searching, browsing, downloading, and sharing biomedical 3D print files, modeling tutorials, and educational material. "Biomedical" includes models of cells, bacteria, or viruses, molecules like proteins or DNA, and anatomical models of organs, tissue, and body parts. The NIH 3D Print Exchange provides models in formats that are readily compatible with 3D printers, and offers a unique set of tools to create and share 3D-printable models related to biomedical science.
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<<<!!!<<< This repository is no longer available. >>>!!!>>> The main objective of our work is to understand the pathomechanisms of late onset neurodegenerative disorders such as Huntington's, Parkinson's, Alzheimer's and Machado Joseph disease and to develop causal therapies for them. The disease causing proteins of these illnesses have been identified, but their functions in the unaffected organism are mostly unknown. Here, we have developed a strategy combining library and matrix yeast two-hybrid screens to generate a highly connected PPI network for Huntington's disease (HD).