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http://www.uniprot.org/uniparc/

Database that contains publicly available protein sequences with stable and unique identifiers (UPI) which are never removed, changed or reassigned. UniParc tracks sequence changes in the source databases and archives the history of all changes. Information other than protein sequence must be retrieved from the UniParc source databases using the database cross-references.

Proper citation: UniParc (RRID:SCR_005818) Copy   

•   Source: SciCrunch Registry

http://202.120.189.88/drvis/

Dr.VIS collects and locates human disease-related viral integration sites. So far, about 600 sites covering 5 virus organisms and 11 human diseases are available. Integration sites in Dr.VIS are located against chromosome, cytoband, gene and refseq position as specific as possible. Viral-cellular junction sequences are extracted from papers and nucleotide databases, and linked to corresponding integration sites Graphic views summarizing distribution of viral integration sites are generated according to chromosome maps. Dr.VIS is built with a hope to facilitate research of human diseases and viruses. Dr.VIS provides curated knowledge of integration sites from chromosome region narrow to genomic position, as well as junction sequences if available. Dr.VIS is an open resource for free.

Proper citation: Dr.VIS - Human Disease-Related Viral Integration Sites (RRID:SCR_005965) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/thornton-srv/databases/FunTree/

FunTree provides a range of data resources to detect the evolution of enzyme function within distant structurally related clusters within domain super families as determined by CATH. To access the resource enter a specific CATH superfamily code or search for a structure / sequence / function (either via a EC code or KEGG ligand / reaction ID, PDB ID or UniProtKB ID). Or browse the resource via superfamily / function / structure / metabolites & reactions via the menu on the left panel. FunTree is a new resource that brings together sequence, structure, phylogenetic, chemical and mechanistic information for structurally defined enzyme superfamilies. Gathering together this range of data into a single resource allows the investigation of how novel enzyme functions have evolved within a structurally defined superfamily as well as providing a means to analyse trends across many superfamilies. This is done not only within the context of an enzyme''''s sequence and structure but also the relationships of their reactions. Developed in tandem with the CATH database, it currently comprises 276 superfamilies covering 1800 (70%) of sequence assigned enzyme reactions. Central to the resource are phylogenetic trees generated from structurally informed multiple sequence alignments using both domain structural alignments supplemented with domain sequences and whole sequence alignments based on commonality of multi-domain architectures. These trees are decorated with functional annotations such as metabolite similarity as well as annotations from manually curated resources such the catalytic site atlas and MACiE for enzyme mechanisms.

Proper citation: FunTree (RRID:SCR_006014) Copy   

•   Source: SciCrunch Registry

http://www.hpppi.iicb.res.in/btox/

Database of Bacterial ExoToxins for Human is a database of sequences, structures, interaction networks and analytical results for 229 exotoxins, from 26 different human pathogenic bacterial genus. All toxins are classified into 24 different Toxin classes. The aim of DBETH is to provide a comprehensive database for human pathogenic bacterial exotoxins. DBETH also provides a platform to its users to identify potential exotoxin like sequences through Homology based as well as Non-homology based methods. In homology based approach the users can identify potential exotoxin like sequences either running BLASTp against the toxin sequences or by running HMMER against toxin domains identified by DBETH from human pathogenic bacterial exotoxins. In Non-homology based part DBETH uses a machine learning approach to identify potential exotoxins (Toxin Prediction by Support Vector Machine based approach).

Proper citation: DBETH - Database for Bacterial ExoToxins for Humans (RRID:SCR_005908) Copy   

•   Source: SciCrunch Registry

http://mint.bio.uniroma2.it/virusmint/

A virus protein interactions database that collects and annotates all the interactions between human and viral proteins and integrates this information in the human protein interaction network. It uses the PSI-MI standard and is fully integrated with the MINT database. You can search for any viral or human protein by entering either common names or database identifiers or display a complete viral interactome.

Proper citation: VirusMINT (RRID:SCR_005987) Copy   

•   Source: SciCrunch Registry

http://img.jgi.doe.gov/cgi-bin/m/main.cgi

Resource for analysis and annotation of genome and metagenome datasets in comprehensive comparative context. IMG provides users with tools for analyzing publicly available genome datasets and metagenome datasets.

Proper citation: IMG System (RRID:SCR_002965) Copy   

•   Source: SciCrunch Registry

http://wwwmgs.bionet.nsc.ru/mgs/systems/rsnp/

A system of databases which stores information on the influence of mutations in regulatory gene regions . This tool helps recognize protein binding sites that are being altered by mutation. It has four cross-linked sub databases that focus on specific aspects including: (1) the effect of single nucleotide mutations in regulatory gene regions and their interaction with nuclear proteins; (2) references to original publications on the subject; (3) the experimental details of these publications; and (4) the protocols of these experiments. This resource is aimed at providing information to further research on the influence of specific sequence alterations on disease susceptibility, drug resistance and healthcare.

Proper citation: rSNP Guide (RRID:SCR_000087) Copy   

•   Source: SciCrunch Registry

http://www.proglycprot.org/

Manually curated, comprehensive repository of experimentally characterized bacterial glycoproteins and archaeal glycoproteins, generated from an exhaustive literature search. This is the focused effort to provide concise relevant information derived from rapidly expanding literature on prokaryotic glycoproteins, their glycosylating enzyme(s), glycosylation linked genes, and genomic context thereof, in a cross-referenced manner. The database is arranged into two sections namely, ProCGP and ProUGP. ProCGP is the main section containing characterized prokaryotic glycoproteins, defined as entries with at least one experimentally known glycosylated residue (glycosite). Whereas, ProUGP is the supplementary section, presenting uncharacterized prokaryotic glycoproteins, defined as entries with experimentally identified glycosylation but unidentified glycosites. The ProGlycProt has been developed with to aid and advance the emerging scientific interests in understanding the mechanisms, implications, and novelties of protein glycosylation in prokaryotes that include many pathogenic as well as economically important bacterial species. The website supports a dedicated structure gallery of homology models and crystal structures of characterized glycoproteins in addition to two new tools developed in view of emerging information about prokaryotic sequons (conserved sequences of amino acids around glycosites) that are never or rarely seen in eukaryotic glycoproteins. ProGlycProt provides an extensive compilation of experimentally identified glycosites (334) and glycoproteins (340) of prokaryotes that could serve as an information resource for research and technology applications in glycobiology. A general data update policy is once in three months. Existing entries are updated in real-time.

Proper citation: ProGlycProt (RRID:SCR_000622) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/dbSTS/

THIS RESOURCE IS NO LONGER IN SERVICE, as of October 1, 2013; however, the site is still accessible. NCBI resource that contains sequence and mapping data on short genomic landmark sequences or Sequence Tagged Sites. STS sequences are incorporated into the STS Division of GenBank. The dbSTS database offers a route for submission of STS sequences to GenBank. It is designed especially for the submission of large batches of STS sequences.

Proper citation: dbSTS (RRID:SCR_000400) Copy   

•   Source: SciCrunch Registry

http://interolog.gersteinlab.org/

Interolog/Regulog quantitatively assess the degree to which interologs can be reliably transferred between species as a function of the sequence similarity of the corresponding interacting proteins.

Proper citation: Interolog/Regulog Database (RRID:SCR_000755) Copy   

•   Source: SciCrunch Registry

http://www.bioguo.org/AnimalTFDB/

A comprehensive transcription factor (TF) database in which they identified and classified all the genome-wide TFs in 50 sequenced animal genomes (Ensembl release version 60). In addition to TFs, it also collects transcription co-factors and chromatin remodeling factors of those genomes, which play regulatory roles in transcription. Here they defined the TFs as proteins containing a sequence-specific DNA-binding domain (DBD) and regulating target gene expression. Currently, the AnimalTFDB classifies all the animal TFs into 72 families according to their conserved DBDs. Gene lists of transcription factors, transcription co-factors and chromatin remodeling factors of each species are available for downloading., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: AnimalTFDB (RRID:SCR_001624) Copy   

•   Source: SciCrunch Registry

https://www.hgmd.cf.ac.uk/ac/introduction.php?lang=english

Curated database of known (published) gene lesions responsible for human inherited disease.

Proper citation: Human Gene Mutation Database (RRID:SCR_001621) Copy   

•   Source: SciCrunch Registry

http://pallab.serc.iisc.ernet.in/gester/

Database of intrinsic terminators of transcription that is comprized of >2,200,000 bacterial terminators identified from a total of 2036 chromosomes and 1508 plasmids. Information about structural parameters of individual terminators such as sequence, length of stem and loop, mismatches and gaps, U-trail, genomic coordinates and gene name and accession number is available in both tabular form and as a composite figure. Summary statistics for terminator profiles of whole genome can be also obtained. Raw data files for individual genomes can be downloaded (.zip files) for detailed investigations. Data is organized into different tiers such that users can fine-tune their search by entering name of the species, or taxon ID or genomes with a certain number of terminators. To visualize the occurrence of the terminators, an interactive map, with the resolution to single gene level, has been developed.

Proper citation: WebGeSTer DB (RRID:SCR_002165) Copy   

•   Source: SciCrunch Registry

http://www.pubgene.org/

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.ecoli-york.org/

A database that curates new experimental and bioinformatic information about the genes and gene products of the model bacterium Escherichia coli K-12 strain MG1655. It has been created to integrate information from post-genomic experiments into a single resource with the aim of providing functional predictions for the 1500 or so gene products for which we have no knowledge of their physiological function. While EchoBASE provides a basic annotation of the genome, taken from other databases, its novelty is in the curation of post-genomic experiments and their linkage to genes of unknown function. Experiments published on E. coli are curated to one of two levels. Papers dealing with the determination of function of a single gene are briefly described, while larger dataset are actually included in the database and can be searched and manipulated. This includes data for proteomics studies, protein-protein interaction studies, microarray data, functional genomic approaches (looking at multiple deletion strains for novel phenotypes) and a wide range of predictions that come out of in silico bioinformatic approaches. The aim of the database is to provide hypothesis for the functions of uncharacterized gene products that may be used by the E. coli research community to further our knowledge of this model bacterium.

Proper citation: EchoBASE (RRID:SCR_002430) Copy   

•   Source: SciCrunch Registry

http://www.tanpaku.org/autophagy/

Database that provides basic, up-to-date information on relevant literature, and a list of autophagy-related proteins and their homologs in eukaryotes.

Proper citation: Autophagy Database (RRID:SCR_002671) Copy   

•   Source: SciCrunch Registry

http://domine.utdallas.edu

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 13,2026. Database of known and predicted protein domain (domain-domain) interactions containing interactions inferred from PDB entries, and those that are predicted by 8 different computational approaches using Pfam domain definitions. DOMINE contains a total of 26,219 domain-domain interactions (among 5,410 domains) out of which 6,634 are inferred from PDB entries, and 21,620 are predicted by at least one computational approach. Of the 21,620 computational predictions, 2,989 interactions are high-confidence predictions (HCPs), 2,537 interactions are medium-confidence predictions (MCPs), and the remaining 16,094 are low-confidence predictions (LCPs). (May 2014)

Proper citation: DOMINE: Database of Protein Interactions (RRID:SCR_002399) Copy   

•   Source: SciCrunch Registry

http://ndbserver.rutgers.edu/

A database of three-dimensional structural information about nucleic acids and their complexes. In addition to primary data, it contains derived geometric data, classifications of structures and motifs, standards for describing nucleic acid features, as well as tools and software for the analysis of nucleic acids. A variety of search capabilities are available, as are many different types of reports. NDB maintains the macromolecular Crystallographic Information File (mmCIF).

Proper citation: Nucleic Acid Database (RRID:SCR_003255) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/RefSeq/

Collection of curated, non-redundant genomic DNA, transcript RNA, and protein sequences produced by NCBI. Provides a reference for genome annotation, gene identification and characterization, mutation and polymorphism analysis, expression studies, and comparative analyses. Accessed through the Nucleotide and Protein databases.

Proper citation: RefSeq (RRID:SCR_003496) Copy   

•   Source: SciCrunch Registry