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http://genome.jouy.inra.fr/spid/
THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. An online database of two-hybrid protein interactions in B. Subtilis. Interactions stored in SPID are either characterized by experimental evidence or by bibliographic references. A graphical user interface is provided to explore interaction networks as well as to view the details of each piece of evidence. The database contains 112 interactions between 79 proteins.
Proper citation: Subtilis Protein interaction Database (RRID:SCR_002123) Copy
It helps users retrieve information on genes and proteins. The underlying structure of PubGene can be viewed as a gene-centric database. Gene and protein names are cross-referenced to each other and to terms that are relevant to understanding their biological function, importance in disease and relationship to chemical substances. The result is a literature network organizing information in a form that is easy to navigate.
Proper citation: PubGene (RRID:SCR_002119) Copy
https://sites.google.com/site/friaptamerstream/
The Aptamer Database is a comprehensive, annotated repository for information about aptamers and in vitro selection. This resource is provided to collect, organize and distribute all the known information regarding aptamer selection. Aptamers are DNA or RNA molecules that have been selected from random pools based on their ability to bind other molecules. Aptamers have been selected which bind nucleic acid, proteins, small organic compounds, and even entire organisms.
Proper citation: Aptamer Database - The Ellington Lab (RRID:SCR_001781) Copy
http://www.ncbi.nlm.nih.gov/cdd
Database of annotations of functional units in proteins including multiple sequence alignment models for ancient domains and full-length proteins. This collection of models includes 3D structures that display the sequence/structure/function relationships in proteins. It also includes alignments of the domains to known three-dimensional protein structures in the MMDB database. The source databases are Pfam, Smart, and COG. Users can identify amino acids in protein sequences with the resources available as well as view single sequences embedded within multiple sequence alignments.
Proper citation: Conserved Domain Database (RRID:SCR_002077) Copy
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. iPfam is a resource that describes physical interactions between those Pfam domains that have a representative structure in the Protein DataBank (PDB). When two or more domains occur within a single structure, the domains are analysed to see if they form an interaction. If the domains are close enough to form an interaction, the bonds that play a role in that interaction are determined. The goal has been to re-calculate iPfam interaction data for each new Pfam release, so that, as Pfam changes, the information within iPfam remains up to date.
Proper citation: Protein families database of alignments and HMMs (RRID:SCR_002115) Copy
http://compbio.cs.toronto.edu/psmdb
Database of non-redundant sets of protein - small-molecule complexes that are especially suitable for structure-based drug design and protein - small-molecule interaction research. PSMB supports: * Support frequent updates - The number of new structures in the PDB is growing rapidly. In order to utilize these structures, frequent updates are required. In contrast to manual procedures which require significant time and effort per update, generation of the PSMDB database is fully automatic thereby facilitating frequent database updates. * Consider both protein and ligand structural redundancy - In the database, two complexes are considered redundant if they share a similar protein and ligand (the protein - small-molecule non-redundant set). This allows the database to contain structural information for the same protein bound to several different ligands (and vice-versa). Additionally, for completeness, the database contains a set of non-redundant complexes when only protein structural redundancy is considered (our protein non-redundant set). The following images demonstrate the structural redundancy of the protein complexes in the PDB compared to the PSMDB. * Efficient handling of covalent bonds -Many protein complexes contain covalently bound ligands. Typically, protein-ligand databases discard these complexes; however, the PSMDB simply removes the covalently bound ligand from the complex, retaining any non-covalently bound ligands. This increases the number of usable complexes in the database. * Separate complexes into protein and ligand files -The PSMDB contains individual structure files for both the protein and all non-covalently bound ligands. The unbound proteins are in PDB format while the individual ligands are in SDF format (in their native coordinate frame).
Proper citation: Protein-Small Molecule Database (RRID:SCR_002112) Copy
http://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-8-335
Cell signaling pathways can be explored using PathFinder, the interactive, online graphical representation of cell signaling pathways. The user can use PathFinder to explore the relationships between different cell signaling pathway components while being presented with our high quality small molecules, antibodies, enzymes, siRNA for gene knockdown and qPCR components to aid them in their research.
Proper citation: Cell Signaling Pathways (RRID:SCR_002070) Copy
A database of new exon boundaries induced by pathogenic mutations in human disease genes.
Proper citation: DBASS (RRID:SCR_002107) Copy
http://www.nih.gov/science/models/rat/
The Rat Genome Program was launched after the National Institutes of Health (NIH) realized the potential of rat models in understanding basic biology and human health and disease. The purpose of this NIH Rat Genomics and Genetics web site is to serve as a central point for information on NIH sponsored and related rat genetic and genomic activities and resources. It will provide information on: the follow up to recommendations made to the NIH; funding opportunities for rat genomic and genetic tools and resources; major rat genomic resources available and/or produced in response to the NIH Rat Program; courses and meetings related to rat genomics and genetics; and selected reports and publications. These programs have produced a wide variety of resources and a way to link and capitalize upon the data and resources of other model organisms and the human. In conjunction with and in addition to these programs, the NIH, through the RGWG, has convened advisory groups and workshops to discuss the opportunities that rat models offer and provide recommendations on the investments that are needed to capitalize on these opportunities.
Proper citation: NIH Rat Genomics and Genetics (RRID:SCR_002267) Copy
http://sarst.life.nthu.edu.tw/cpdb/
A database of circular permutation (CP) in proteins that provides resources for studying circular permutation (CP) and circular permutation relationships among protein structures. This site also offers viable CP site predictions in order to facilitate the application of CP in academic researches and biotechnological developments.
Proper citation: CPDB - the Circular Permutation Database (RRID:SCR_002261) Copy
http://cancer.sanger.ac.uk/cancergenome/projects/cosmic/
Database to store and display somatic mutation information and related details and contains information relating to human cancers. The mutation data and associated information is extracted from the primary literature. In order to provide a consistent view of the data a histology and tissue ontology has been created and all mutations are mapped to a single version of each gene. The data can be queried by tissue, histology or gene and displayed as a graph, as a table or exported in various formats.
Some key features of COSMIC are:
* Contains information on publications, samples and mutations. Includes samples which have been found to be negative for mutations during screening therefore enabling frequency data to be calculated for mutations in different genes in different cancer types.
* Samples entered include benign neoplasms and other benign proliferations, in situ and invasive tumours, recurrences, metastases and cancer cell lines.
Proper citation: COSMIC - Catalogue Of Somatic Mutations In Cancer (RRID:SCR_002260) Copy
Collection of data of protein sequence and functional information. Resource for protein sequence and annotation data. Consortium for preservation of the UniProt databases: UniProt Knowledgebase (UniProtKB), UniProt Reference Clusters (UniRef), and UniProt Archive (UniParc), UniProt Proteomes. Collaboration between European Bioinformatics Institute (EMBL-EBI), SIB Swiss Institute of Bioinformatics and Protein Information Resource. Swiss-Prot is a curated subset of UniProtKB.
Proper citation: UniProt (RRID:SCR_002380) Copy
THIS RESOURCE IS NO LONGER IN SERVICE, documented on April 26, 2011. Neurons are characterized in terms of their morphological, physiological and gene expression profiles. Synaptic connections are characterized in terms of their physiological and anatomical profiles. Neuron morphology profiles are obtained from detailed morphometric breakdown of 3D reconstructed neurons (m-Profiles), neuron physiology profiles are obtained from detailed measurement of the electrophysiological responses to a series of stimulus protocols (e-Profiles), and neuron gene expression profiles are obtained from single cell RT-PCR data (g-Profiles) and in the near future from gene-chips. Synaptic connections are characterized by the identity of the pre and postsynaptic neurons (sn-Profile), the anatomy of synaptic connections as characterized by the axonal and dendritic location of light microscopically identified putative synapses (sm-Profile), and the physiology of synaptic connections as characterized by a profile of electrophysiological parameters obtained from a series of stimulation protocols applied to the presynaptic neuron (se-Profile).
Proper citation: Neocortical Microcircuit Database (RRID:SCR_002415) Copy
http://www.ebi.ac.uk/swissprot/hpi/hpi.html
THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 03, 2011. IT HAS BEEN REPLACED BY A NEW UniProtKB/Swiss-Prot ANNOTATION PROGRAM CALLED UniProt Chordata protein annotation program. The Human Proteome Initiative (HPI) aims to annotate all known human protein sequences, as well as their orthologous sequences in other mammals, according to the quality standards of UniProtKB/Swiss-Prot. In addition to accurate sequences, we strive to provide, for each protein, a wealth of information that includes the description of its function, domain structure, subcellular location, similarities to other proteins, etc. Although as complete as currently possible, the human protein set they provide is still imperfect, it will have to be reviewed and updated with future research results. They will also create entries for newly discovered human proteins, increase the number of splice variants, explore the full range of post-translational modifications (PTMs) and continue to build a comprehensive view of protein variation in the human population. The availability of the human genome sequence has enabled the exploration and exploitation of the human genome and proteome to begin. Research has now focused on the annotation of the genome and in particular of the proteome. With expert annotation extracted from the literature by biologists as the foundation, it has been possible to expand into the areas of data mining and automatic annotation. With further development and integration of pattern recognition methods and the application of alignments clustering, proteome analysis can now be provided in a meaningful way. These various approaches have been integrated to attach, extract and combine as much relevant information as possible to the proteome. This resource should be valuable to users from both research and industry. We maintain a file containing all human UniProtKB/Swiss-Prot entries. This file is updated at every biweekly release of UniProt and can be downloaded by FTP download, HTTP download or by using a mirroring program which automatically retrieves the file at regular intervals.
Proper citation: Human Proteomics Initiative (RRID:SCR_002373) Copy
International Committee on Taxonomy of Viruses (ICTV) is charged by the Virology Division of the International Union of Microbiological Societies (IUMS) with developing, refining, and maintaining the official, universal taxonomy of all viruses. The goal is to classify and name all known viruses into a single taxonomy that reflects their evolutionary relationships. It provides a variety of resources in support of that goal including online and downloadable versions of current and historical releases of the virus taxonomy.
Proper citation: International Committee on Taxonomy of Viruses (RRID:SCR_002377) Copy
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 4,2023.The Human Gene and Protein Database presents SDS-PAGE patterns and other informations of human genes and proteins. The HGPD was constructed from full-length cDNAs. For conversion to Gateway entry clones, we first determined an open reading frame (ORF) region in each cDNA meeting the criteria. Those ORF regions were PCR-amplified utilizing selected resource cDNAs as templates. All the details of the construction and utilization of entry clones will be published elsewhere. Amino acid and nucleotide sequences of an ORF for each cDNA and sequence differences of Gateway entry clones from source cDNAs are presented in the GW: Gateway Summary window. Utilizing those clones with a very efficient cell-free protein synthesis system featuring wheat germ, we have produced a large number of human proteins in vitro. Expressed proteins were detected in almost all cases. Proteins in both total and supernatant fractions are shown in the PE: Protein Expression window. In addition, we have also successfully expressed proteins in HeLa cells and determined subcellular localizations of human proteins. These biological data are presented on the frame of cDNA clusters in the Human Gene and Protein Database. To build the basic frame of HGPD, sequences of FLJ full-length cDNAs and others deposited in public databases (Human ESTs, RefSeq, Ensembl, MGC, etc.) are assembled onto the genome sequences (NCBI Build 35 (UCSC hg17)). The majority of analysis data for cDNA sequences in HGPD are shared with the FLJ Human cDNA Database (http://flj.hinv.jp/) constructed as a human cDNA sequence analysis database focusing on mRNA varieties caused by variations in transcription start site (TSS) and splicing.
Proper citation: Human Gene and Protein Database (HGPD) (RRID:SCR_002889) Copy
Bibliographic database that brings together free, full-text scholarly articles from hundreds of universities and colleges worldwide. Curated by university librarians and their supporting institutions, the Network includes a growing collection of peer-reviewed journal articles, book chapters, dissertations, working papers, conference proceedings, and other original scholarly work. A central discipline wheel features ten color-coded disciplines: law, social and behavioral sciences, arts and humanities, life sciences, physical sciences and mathematics, education, engineering, medicine and health sciences, business, and architecture. The size of each color-coded area reflects the size of each discipline's collection relative to the rest of DCN. Users can click on any segment of any layer of the wheel, with the selected discipline, subdiscipline, or subject navigating users to their chosen commons area where they can then proceed to a list of full-text PDFs. To be clear, typing a couple of keywords into the Search Entire Network box, also located on the homepage, might be a more efficient method than mousing around on this graphical browsing element. If you would like to contribute your institution's research to the Digital Commons Network, Use the form provided, http://network.bepress.com/about/
Proper citation: Digital Commons Network (RRID:SCR_002646) Copy
https://simtk.org/home/nmblmodels
The goal of the neuromuscular models library is to provide a resource for students, researchers, and clinicians to access, use, test, and develop models. The majority of models in this library are for use with OpenSIM and/or SIMM. Users who contribute models to the database can set up a project page where they can track who is using the model and contact with them.
Proper citation: Neuromuscular Models Library (RRID:SCR_002682) Copy
http://bioinfo.au.tsinghua.edu.cn/dbRES/
dbRES is a web-oriented comprehensive database for RNA Editing Site. dbRES contain only experimental validated RNA Editing Site. All the data in dbRES was manually collected from literatures reporting related experiment result or the GeneBank database. dbRES now contains all together 5437 RNA edit site data. dbRES covers altogether 95 organisms from 251 transcripts. RNA editing is a post-transcriptional modification of RNA and markedly increases the complexity of the transcriptome. RNA editing occurs in the nucleus, as well as in mitochondria and plastids. To date such changes have been observed in prokaryotes, plants, animals and virus. The diversity of this widespread phenomenon includes nucleoside modifications, nucleotide additions and insertions, either in coding or non-coding sequences of RNA, which can occur concomitantly with transcription and splicing processes.
Proper citation: dbRES: A web-oriented database for annotated RNA Editing Site (RRID:SCR_002322) Copy
http://bibiserv.techfak.uni-bielefeld.de/agt-sdp/
Database providing automatic test cases for protein-protein docking. A consensus-type approach is proposed processing the whole PDB and classifying protein structures into complexes and unbound proteins by combining information from three different approaches. Out of this classification test cases are generated automatically. All calculations were run on the database. The information stored is available via a web interface. The user can choose several criteria for generating his own subset out of the test cases, e.g. for testing docking algorithms. In unbound protein--protein docking, the complex of two proteins is predicted using the unbound conformations of the proteins (Halperin et al.,2002). For testing of docking algorithms, two unbound proteins which form a known complex have to be identified, so that the result of the docking algorithm can be compared to the known complex. For the identification of test cases, the structures taken from the PDB have to be classified as unbound proteins or complexes and unbound proteins with a 100% sequence identity to one complex part have to be searched. By now, most groups use handpicked test sets. The largest collection of test cases used so far is described by Chen et al. (Chen et al.,2003) and contains 31 test cases for unbound docking. Because of the exponential growth of available protein structures in the PDB, automatic generation of test cases will become more and more important in the future.
Proper citation: Automatic Generated Test-Sets Database for Protein-Protein Docking (RRID:SCR_002281) Copy
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