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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
http://wwwmgs.bionet.nsc.ru/mgs/gnw/aspd/
THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 04, 2014. Curated database on selected from randomized pools proteins and peptides designed for accumulation of experimental data on protein functionality obtained by in vitro directed evolution methods (phage display, ribosome display, SIP etc.) ASPD is integrated by means of hyperlinks with different databases (SWISS-PROT, PDB, PROSITE, etc). The database also contains modules for pairwise correlation analysis and BLAST search.
Proper citation: Artificial Selected Proteins/Peptides Database (RRID:SCR_007557) Copy
Nature Precedings is a free online service from NPG that enables researchers in the life sciences to openly share preliminary findings, disseminate emerging results, solicit community feedback, and claim priority over discoveries by posting preprint manuscripts, white papers, technical reports, posters, and presentations. It is a permanent, citable archive for pre-publication research and preliminary findings.
Proper citation: Nature Precedings (RRID:SCR_007438) Copy
http://bond.unleashedinformatics.com/
THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone.. Documented on August 19,2019.BOND, which requires registration of a free account, is a resource used to perform cross-database searches of available sequence, interaction, complex and pathway information. BOND integrates a range of component databases including GenBank and BIND, the Biomolecular Interaction Network Database. BOND contains 70+ million biological sequences, 33,000 structures, 38,000 GO terms, and over 200,000 human curated interactions contained in BIND, and is open access. BOND serves the interests of the developing global interactome effort encompassing the genomic, proteomic and metabolomic research communities. BOND is the first open access search resource to integrate sequence and interaction information. BOND integrates BLAST functionality, and contains a well-documented API. BOND also stores annotation links for sequences, including links to Genome Ontology descriptions, MedLine abstracts, taxon identifiers, associated structures, redundant sequences, sequence neighbors, conserved domains, data base cross-references, Online Mendalian Inheritance in Man identifiers, LocusLink identifiers and complete genomes. BIND on BOND The Biomolecular Interaction Network Database (BIND), a component database of BOND, is a collection of records documenting molecular interactions. The contents of BIND include high-throughput data submissions and hand-curated information gathered from the scientific literature. BIND is an interaction database with three classifications for molecular associations: molecules that associate with each other to form interactions, molecular complexes that are formed from one or more interaction(s) and pathways that are defined by a specific sequence of two or more interactions.Interactions A BIND record represents an interaction between two or more objects that is believed to occur in a living organism. A biological object can be a protein, DNA, RNA, ligand, molecular complex, gene, photon or an unclassified biological entity. BIND records are created for interactions which have been shown experimentally and published in at least one peer-reviewed journal. A record also references any papers with experimental evidence that support or dispute the associated interaction. Interactions are the basic units of BIND and can be linked together to form molecular complexes or pathways. The BIND interaction viewer is a tool to visualize and analyze molecular interactions, complexes and pathways. The BIND interaction viewer uses Ontoglyphs to display information about a protein via attributes such as molecular function, biological process and sub-cellular localization. Ontoglyphs allow to graphically and interactively explore interaction networks, by visualizing interactions in the context of 34 functional, 25 binding specificity and 24 sub-cellular localization Ontoglyphs categories. We will continue to provide an open access version of BOND, providing its subscribers with free, unlimited access to a core content set. But we are confident you will soon want to upgrade to BONDplus.
Proper citation: Biomolecular Object Network Databank (RRID:SCR_007433) Copy
http://www.eurasnet.info/tools/asdatabases
It has been established with the intention of assembling in a central, publicly accessible site information about alternatively spliced genes, their products and expression patterns. Version 2.1 of ASDB consists of two divisions, ASDB(proteins) , which contains amino acid sequences, and ASDB(nucleotides) with genomic sequences.
SWISS-PROT uses two formats for description of alternative splicing Thus the protein sequences were selected from SWISS-PROT using full text search for both the words alternative splicing (usually in the CC lines) and varsplic (in the FT lines). In order to group proteins that could arise by alternative splicing of the same gene, we developed the clustering procedure. Two proteins were linked if they had a common fragment of at least 20 amino acids, and clusters were initially defined as maximum connected groups of linked proteins. It turned out that some clusters were chimeric, in the sense that they contained members of multi-gene families, but not alternatively spliced variants of one gene. Therefore the multiple alignments were subject to additional analysis aimed at detection of chimeric clusters.
Each cluster is represented by multiple alignment of its members constructed using CLUSTALW. The distribution of cluster size, representation of species and other relevant statistics of ASDB(proteins) can be accessed through the links below.
This processing covers the cases when alternatively spliced variants are described in separate SWISS-PROT entries. The other kinds of ASDB records, originating from the SWISS-PROT entries with the varsplic field in the feature table, usually describe the proteins that are not part of any cluster. In these cases, the information on the variable fragments of the several proteins which result from the alternative splicing of a single gene is contained in the entry itself. ASDB(proteins) entries are marked with different symbols to allow for easy differentiation among the three types: those proteins which are part of the ASDB clusters and the corresponding multialignments, those which have the information on different variants in the associated SWISS-PROT entries, and those for which the information on the variants is not available at the present time. ASDB contains internal links between entries and/or clusters, as well as external links to Medline, GenBank and SWISS-PROT entries.
The ASDB(nucleotides) division was generated by collecting all GenBank entries containing the words alternative splicing and further selection of those entries that contain complete gene sequences (all CDS fields are complete, i.e. they do not have continuation signs).
Sponsors: This work was supported by the Director, Office of Energy Research, Office of Biological and Environmental Research, of the US Department of Energy under Contract No. DE-ACO3-76SF00098. Additional support came from grants from the Russian Fund of Basic Research (99-04-48347), the Russian State Scientific Program Human Genome (65/99), and the Merck Genome Research Institute (244).
Proper citation: Alternative Splicing Database (RRID:SCR_007555) Copy
http://cocomac.g-node.org/main/index.php?
Online access (html or xml) to structural connectivity ("wiring") data on the Macaque brain. The database has become by far the largest of its kind, with data extracted from more than four hundred published tracing studies. The main database, contains data from tracing studies on anatomical connectivity in the macaque cerebral cortex. Also available are a variety of tools including a graphical simulation workbench, map displays and the CoCoMac-Paxinos-3D viewer. Submissions are welcome. To overcome the problem of divergent brain maps ORT (Objective Relational Transformation) was developed, an algorithmic method to convert data in a coordinate- independent way based on logical relations between areas in different brain maps. CoCoMac data is used to analyze the organization of the cerebral cortex, and to establish its structure- function relationships. This includes multi-variate statistics and computer simulation of models that take into account the real anatomy of the primate cerebral cortex. This site * Provides full, scriptable open access to the data in CoCoMac (you must adhere to the citation policy) * Powers the graphical interface to CoCoMac provided by the Scalable Brain Atlas * Sports an extensive search/browse wizard, which automatically constructs complex search queries and lets you further explore the database from the results page. * Allows you to get your hands dirty, by using the custom SQL query service. * Displays connectivity data in tabular form, through the axonal projections service. CoCoMac 2 was initiated at the Donders Institute for Brain, Cognition and Behaviour, and is currently supported by the German neuroinformatics node and the Computational and Systems Neuroscience group at the Juelich research institute.
Proper citation: CoCoMac (RRID:SCR_007277) Copy
http://www.sbg.bio.ic.ac.uk/3dgenomics/searchpage1.cgi
THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. Database containing structural annotations for the proteomes of just under 100 organisms. Using data derived from public databases of translated genomic sequences, representatives from the major branches of Life are included: Prokaryota, Eukaryota and Archaea. The annotations stored in the database may be accessed in a number of ways. The help page provides information on how to access the database. 3D-GENOMICS is now part of a larger project, called e-Protein. The project brings together similar databases at three sites: Imperial College London , University College London and the European Bioinformatics Institute . e-Protein''s mission statement is To provide a fully automated distributed pipeline for large-scale structural and functional annotation of all major proteomes via the use of cutting-edge computer GRID technologies. The following databases are incorporated: NRprot, SCOP, ASTRAL, PFAM, Prosite, taxonomy, COG The following eukaryotic genomes are incorporated: Anopheles gambiae, protein sequences from the mosquito genome; Arabidopsis thaliana, protein sequences from the Arabidopsis genome; Caenorhabditis briggsae, protein sequences from the C.briggsae genome; Caenorhabditis elegans protein sequences from the worm genome; Ciona intestinalis protein sequences from the sea squirt genome; Danio rerio protein sequences from the zebrafish genome; Drosophila melanogaster protein sequences from the fruitfly genome; Encephalitozoon cuniculi protein sequences from the E.cuniculi genome; Fugu rubripes protein sequences from the pufferfish genome; Guillardia theta protein sequences from the G.theta genome; Homo sapiens protein sequences from the human genome; Mus musculus protein sequences from the mouse genome; Neurospora crassa protein sequences from the N.crassa genome; Oryza sativa protein sequences from the rice genome; Plasmodium falciparum protein sequences from the P.falciparum genome; Rattus norvegicus protein sequences from the rat genome; Saccharomyces cerevisiae protein sequences from the yeast genome; Schizosaccharomyces pombe protein sequences from the yeast genome
Proper citation: 3D-Genomics Database (RRID:SCR_007430) Copy
http://www.agbase.msstate.edu/
A curated, open-source, web-accessible resource for functional analysis of agricultural plant and animal gene products. Our long-term goal is to serve the needs of the agricultural research communities by facilitating post-genome biology for agriculture researchers and for those researchers primarily using agricultural species as biomedical models. AgBase provides tools designed to assist with the analysis of proteomics data and tools to evaluate experimental datasets using the GO. Additional tools for sequence analysis are also provided. We use controlled vocabularies developed by the Gene Ontology (GO) Consortium to describe molecular function, biological process, and cellular component for genes and gene products in agricultural species. AgBase will also accept annotations from any interested party in the research communities. AgBase develops freely available tools for functional analysis, including tools for using GO. We appreciate any and all questions, comments, and suggestions. AgBase uses the NCBI Blast program for searches for similar sequences. And the Taxonomy Browser allows users to find the NCBI defined taxon ID for or taxon name for different organisms.
Proper citation: AgBase (RRID:SCR_007547) Copy
THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. The 7 database (or a7db) provides physiological, pharmacological and structural data pertaining to the 7 subunit of the nicotinic acetylcholine receptor. As well as the simple boolean-based query, there are several other ways to help you interrogate the database; * One page query builder * Query builder based on the category of data * Upload a prebuilt/previous query * Browse the database To gain insight into what sort of data can be queried, the one page or categorized query builders are recommended. Or you can just browse the database. The best way to navigate is to use the links on the left. Please be aware that we are presenting the raw data and that it is up to the user on how best to interpret that data. You can read more about the database in the recent article in BMC Neuroscience
Proper citation: Alpha-7 Database (RRID:SCR_007300) Copy
http://biobases.ibch.poznan.pl/5SData/
A database on nucleotide sequences of 5S rRNAs and their genes. The database contains 1985 primary structures of 5S rRNA and 5S rDNA, and was last updated in 2002, according to the website. They include 60 archaebacterial, 470 eubacterial, 63 plastid, nine mitochondrial and 1383 eukaryotic sequences. The nucleotide sequences of the 5S rRNAs or 5S rDNAs are divided according to the taxonomic position of the source organisms. The sequences for particular organisms can be retrieved as single files using a taxonomic browser or in multiple sequence structural alignments. The multiple sequence alignments of 5S ribosomal RNAs can be downloaded in TAB-delimited and FASTA formats.
Proper citation: 5S Ribosomal RNA Database (RRID:SCR_007545) Copy
Project aimed at making neuroimaging data sets of brain freely available to scientific community. By compiling and freely distributing neuroimaging data sets, future discoveries in basic and clinical neuroscience are facilitated.
Proper citation: Open Access Series of Imaging Studies (RRID:SCR_007385) Copy
http://www.jncasr.ac.in/cremofac/
CREMOFAC is a database for chromatin remodeling factors has been developed. The database harbors 64 types of remodeling factors from 49 different organisms reported in literature and facilitates a comprehensive search for them. In addition, it also provides in-depth information for the factors reported in the three widely studied mammals namely, human, mouse and rat. Further, information on literature, pathways, and phylogenetic relationships has also been covered.
Proper citation: CREMOFAC: A web-database of Chromatin Remodeling Factors (RRID:SCR_007613) Copy
http://pgrc.ipk-gatersleben.de/cr-est
The Crop EST Database (CR-EST) is a public available online resource providing access to sequence, classification, clustering, and annotation data of crop EST projects at the IPK. Summarized numbers about genomic data of species are listed in tables. The main database content is original sequence data and cDNA library information from different organisms as well as results from BlastX searches against major protein sequence databases contained in NRPEP. Additionally sequence alignments of stackPACK clustering projects are available. This web application allows to BLAST against CR-EST ESTs and to query and retrieve data from Gene Ontology and metabolic pathway annotations as well as sequence similarities from stored results of BLASTX searches against the NRPEP database. CR-EST also features interactive JAVA-based tools, such as open reading frame visualization and explorative analysis of Gene Ontology mappings to ESTs.
Proper citation: CR-EST - Crop ESTs (RRID:SCR_007612) Copy
http://www.ncbi.nlm.nih.gov/Web/Newsltr/Spring04/cancer.html
Cancer Chromosomes is an integration of three databases, the NCI/NCBI SKY/M-FISH & CGH Database, the NCI Mitelman Database of Chromosome Aberrations in Cancer, and the NCI Recurrent Aberrations in Cancer, which all focus on various aspects of cancer and cancer genes. The goal of the SKY/M-FISH and CGH database is to provide a public platform for investigators to share and compare their molecular cytogenetic data. The database is open to everyone and all users can view an individual investigator''s public data or compare public cases from different investigators. The information in the Mitelman Database of Chromosome Aberrations in Cancer relates chromosomal aberrations to tumor characteristics, based either on individual cases or associations. All the data have been manually culled from the literature. Complete karyotypes, patient characteristics, and references are found in the Mitelman Database of Chromosome Aberrations in Cancer. Users can search all three databases for cytogenetic, clinical, and/or reference information.
Proper citation: Cancer Chromosomes (RRID:SCR_007575) Copy
http://www.mrc-lmb.cam.ac.uk/genomes/FlyTF/
The FlyTF database contains information on the manual curation of FlyBase identifiers based on FlyBase/Gene Ontology annotation or the DBD Transcription Factor Database. FlyBase identifiers are putative site-specific transcription factors. There are currently1052 of them in this database.
Proper citation: FlyTF (RRID:SCR_007611) Copy
THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 15, 2013. Non-coding DNA segments that are conserved across multiple homologous genomic sequences are good indicators of putative regulatory elements. We use a systematic approach to delineate such conserved non-coding blocks from a collection of vertebrate species. Upstream regions of homologous gene pairs from man, rhesus monkey, mouse, rat, dog, cow, chicken, tetraodon, zebrafish and xenopus are considered for this purpose. Pairwise as well as Multiple alignments based on the pairwise ones are available. Sequence conservation in non-coding, upstream regions of orthologous genes from man and mouse is likely to reflect common regulatory DNA sites. Motivated by this assumption we have delineated a catalogue of conserved non-coding sequence blocks and provide the CORG-''COmparative Regulatory Genomics''-database. The data were computed based on statistically significant local suboptimal alignments of 15 kb regions upstream of the translation start sites of, currently, 10 793 pairs of orthologous genes. The resulting conserved non-coding blocks were annotated with EST matches for easier detection of non-coding mRNA and with hits to known transcription factor binding sites. CORG data are accessible from the ENSEMBL web site via a DAS service as well as a specially developed web service for query and interactive visualization of the conserved blocks and their annotation.
Proper citation: CORG - A database for COmparative Regulatory Genomics (RRID:SCR_007610) Copy
HubMed provides an interface to PubMed. Quick access to searches with a Firefox search plugin or a HubMed bookmarklet (drag to your browser''s bookmarks toolbar). Export citations in RIS, BibTeX, RDF and MODS formats, or directly to RefWorks. Unzip HubMed''s import filter into Endnote''s Filters folder for direct import into Endnote, or install the RIS Export plugin for direct import into ProCite, RefMan and older versions of Endnote. Use the Citation Finder to convert reference lists from PDFs into search results. Create lists of closely related papers using Rank Relations, then visualise and browse clusters of related papers using TouchGraph (requires Java). Graph occurrences of keywords in published papers over time. Tag and store annotated metadata for articles of interest.
Proper citation: HubMed (RRID:SCR_007296) Copy
http://genome.mc.pref.osaka.jp/BGED/
THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 08, 2011. This database contains gene expression data for various physiological and pathological processes in mouse brain. All the data have been obtained by adaptor-tagged competitive PCR, an advanced version of quantitative PCR. Brain Gene Expression Database (BGED) contains gene expression data for various physiological and pathological processes in mouse brain. All the data have been obtained by adaptor-tagged competitive PCR, an advanced version of quantitative PCR. Manual Download 1. Data retrieval Gene expression data can be retrieved either by ID numbers or by keywords representing functional annotations from this page. The ID numbers include GenBank, RefSeq, SwissProt, Gene Ontology, and BED (our own ID). The keyword search is based either on definition in GenBank, SwissProt and RefSeq, functional annotation of SwissProt database, or Gene Ontology terms. 2. Gene expression pattern display * Display of multiple gene expression patterns. Expression patterns of multiple genes selected by the keyword search can be displayed from the result page of the keyword search. * Gene expression pattern similarity search This function is available on the information page of each gene accessed through BED ID (in-house ID).
Proper citation: Brain Gene Expression Database (RRID:SCR_007299) Copy
http://genolist.pasteur.fr/Colibri/
Database dedicated to the analysis of the genome of Escherichia coli. Its purpose is to collate and integrate various aspects of the genomic information from E. coli, the paradigm of Gram-negative bacteria. Colibri provides a complete dataset of DNA and protein sequences derived from the paradigm strain E. coli K-12, linked to the relevant annotations and functional assignments. It allows one to easily browse through these data and retrieve information, using various criteria (gene names, location, keywords, etc.). The data contained in Colibri originates from two major sources of information, the reference genomic DNA sequence from the E. coli Genome Project and the feature annotations from the EcoGene data collection., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: Colibri (RRID:SCR_007606) Copy
Comparasite is an integrated database of our original full-length cDNA sequence data. It consists of seven sub-databases of apicomplexa protozoa, Plasmodium falciparum, Plasmodium yoelii, Plasmodium vivax, Toxoplasma gondii, Cryptosporidium parvum, Echinococcus multilocularis. Homologous gene groups are clustered and comparative analysis of any combination of these seven species is implemented, such as interspecies comparisons as to cellular localization, motifs or transmembrane regions and so on. For submitted keywords and other search conditions, Comparasite retrieves orthologous gene groups containing a given protein motif/GO term etc in common or in a species-specific manner. By enabling multi-faceted comparative analyses of genes of apicomplexa protozoa, monophyletic organisms that have evolved to diversify to parasitize various hosts by adopting complex life cycles, Comparasite should help elucidate the mechanism behind parasitism.
Proper citation: Comparasite: full length cDNA database (RRID:SCR_007608) Copy
THIS RESOURCE IS NO LONGER IN SERVICE, documented August 26, 2016. CoC Central is a searchable database of residue conservation data covering the universe of known protein structures. CoC is useful for identifying functionally, kinetically, and thermodynamically important residues. Knowledge of universally conserved positions in protein folds may aid in identifying positions of kinetic or thermodynamic importance in protein folding, as well as those with a functional role.
Proper citation: CoC Central (RRID:SCR_007602) Copy
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