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http://amp.pharm.mssm.edu/datasets2tools/

Database for the discovery and evaluation of biomedical digital objects. It includes a wide variety of enrichment analyses, gene interaction networks, interactive data visualizations, datasets, and computational tools.

Proper citation: Datasets2Tools (RRID:SCR_016174) Copy   

•   Source: SciCrunch Registry

http://www.cuilab.cn/transmir

Collection of transcription factor microRNA regulations. TransmiR v2.0 manually curated TF-miRNA regulations from publications during 2013-2017 and included ChIP-seq-derived TF-miRNA regulation data.

Proper citation: TransmiR (RRID:SCR_017499) Copy   

•   Source: SciCrunch Registry

https://www.hmtvar.uniba.it

Manually curated database offering variability and pathogenicity information about mtDNA variants. Human mitochondrial variants data of healthy and diseased subjects.Data and text mining pipeline to annotate human mitochondrial variants with functional and clinical information.

Proper citation: HmtVar (RRID:SCR_017288) Copy   

•   Source: SciCrunch Registry

http://bloodexposome.org

Collection of chemical compounds and associated information that were automatically extracted by text mining content of PubMed and PubChem databases. Unifies chemical lists from metabolomics, systems biology, environmental epidemiology, occupational expossure, toxiology and nutrition fields.

Proper citation: Blood Exposome Database (RRID:SCR_017610) 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://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.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://www.homozygositymapper.org/

A web-based approach of homozygosity mapping that can handle tens of thousands markers. User can upload their own SNP genotype files to the database. Intuitive graphic interface is provided to view the homozygous stretches, with the ability of zooming into single chromosomes or user-defined chromosome regions. The underlying genotypes in all samples are displayed. The software is also integrated with our candidate gene search engine, GeneDistiller, so that users can interactively determine the most promising gene. (entry from Genetic Analysis Software)

Proper citation: HOMOZYGOSITYMAPPER (RRID:SCR_001714) 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://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://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://genetrail.bioinf.uni-sb.de/

A web-based application that analyzes gene sets for statistically significant accumulations of genes that belong to some functional category. Considered category types are: KEGG Pathways, TRANSPATH Pathways, TRANSFAC Transcription Factor, GeneOntology Categories, Genomic Localization, Protein-Protein Interactions, Coiled-coil domains, Granzyme-B clevage sites, and ELR/RGD motifs. The web server provides two statistical approaches, "Over-Representation Analysis" (ORA) comparing a reference set of genes to a test set, and "Gene Set Enrichment Analysis" (GSEA) scoring sorted lists of genes., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GeneTrail (RRID:SCR_006250) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.intec.ugent.be/magic/

Web based interface for exploring and analyzing a comprehensive maize-specific cross-platform expression compendium. This compendium was constructed by collecting, homogenizing and formally annotating publicly available microarrays from Gene Expression Omnibus (GEO), and ArrayExpress.

Proper citation: Magic (RRID:SCR_006406) Copy   

•   Source: SciCrunch Registry

http://www.bioinsilico.org/cgi-bin/CAPSDB/staticHTML/home

It is a structural classification of helix-cappings or caps compiled from protein structures. Caps extracted from protein structures have been structurally classified based on geometry and conformation and organized in a tree-like hierarchical classification where the different levels correspond to different properties of the caps. CASP-DB is fully browsable and searchable and is regularly updated. The regions of the polypeptide chain immediately preceding or following a helix are known as Nt- and Ct cappings, respectively. Cappings play a central role stabilizing helices due to lack of intrahelical hydrogen bonds in the first and last turn. Sequence patterns of amino acid type preferences have been derived for cappings but the structural motifs associated to them are still unclassified. CAPS-DB is a database of clusters of structural patterns of different capping types. The clustering algorithm is based in the geometry and the space conformation of these regions. CAPS-DB is a relational database that allows the user to search, browse, inspect and retrieve structural data associated to cappings. The contents of CAPS-DB might be of interest to a wide range of scientist covering different areas such as protein design and engineering, structural biology and bioinformatics. CapsDB v4.0 * PDB structures: 4591 * Number of clusters: 859 * Number of caps: 31452

Proper citation: CAPS Database (RRID:SCR_006862) Copy   

•   Source: SciCrunch Registry

http://scop.mrc-lmb.cam.ac.uk/scop/

The Structural Classification of Proteins (SCOP) database is a comprehensive ordering of all proteins of known structure, according to their evolutionary and structural relationships. Protein domains in SCOP are hierarchically classified into families, superfamilies, folds and classes. The continual accumulation of sequence and structural data allows more rigorous analysis and provides important information for understanding the protein world and its evolutionary repertoire. SCOP participates in a project that aims to rationalize and integrate the data on proteins held in several sequence and structure databases. As part of this project, starting with release 1.63, we have initiated a refinement of the SCOP classification, which introduces a number of changes mostly at the levels below superfamily. The pending SCOP reclassification will be carried out gradually through a number of future releases. In addition to the expanded set of static links to external resources, available at the level of domain entries, we have started modernization of the interface capabilities of SCOP allowing more dynamic links with other databases.

Proper citation: SCOP: Structural Classification of Proteins (RRID:SCR_007039) Copy   

•   Source: SciCrunch Registry

https://myhits.sib.swiss/

Database devoted to protein domains. It is also a collection of tools for the investigation of the relationships between protein sequences and motifs described on them.

Proper citation: MyHits (RRID:SCR_006757) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.biol.uoa.gr/cuticleDB

A relational database containing all structural proteins of Arthropod cuticle identified to date. Many come from direct sequencing of proteins isolated from cuticle and from sequences from cDNAs that share common features with these authentic cuticular proteins. It also includes proteins from the five sequenced genomes where manual annotation has been applied to cuticular proteins: Anopheles gambiae, Apis mellifera, Bombyx mori, Drosophila melanogaster, and Nasonia vitripennis. Some sequences were confirmed as authentic cuticular proteins because protein sequencing revealed that they were present in cuticle; others were identified by sequence homology and other criteria. Entries provides information about whether sequences are putative or authentic cuticular proteins. CuticleDB was primarily designed to contain correct and full annotation of cuticular protein data. The database will be of help to future genome annotators. Users will be able to test hypotheses for the existence of known and also of yet unknown motifs in cuticular proteins. An analysis of motifs may contribute to understanding how proteins contribute to the physical properties of cuticle as well as to the precise nature of their interaction with chitin.

Proper citation: CuticleDB (RRID:SCR_007045) Copy   

•   Source: SciCrunch Registry