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http://www.unihi.org

A database of human molecular interaction networks that integrates human protein-protein and transcriptional regulatory interactions from 15 distinct resources and aims to give direct and easy access to the integrated data set and to enable users to perform network-based investigations. The database includes tools (i) to search for molecular interaction partners of query genes or proteins in the integrated dataset, (ii) to inspect the origin, evidence and functional annotation of retrieved proteins and interactions, (iii) to visualize and adjust the resulting interaction network, (iv) to filter interactions based on method of derivation, evidence and type of experiment as well as based on gene expression data or gene lists and (v) to analyze the functional composition of interaction networks.

Proper citation: Unified Human Interactome (RRID:SCR_005805) Copy   

•   Source: SciCrunch Registry

http://deepbase.sysu.edu.cn/chipbase/

A database for decoding transcription factor binding maps, expression profiles and transcriptional regulation of long non-coding RNAs (lncRNAs, lincRNAs), microRNAs, other ncRNAs (snoRNAs, tRNAs, snRNAs, etc.) and protein-coding genes from ChIP-Seq data. ChIPBase currently includes millions of transcription factor binding sites (TFBSs) among 6 species. ChIPBase provides several web-based tools and browsers to explore TF-lncRNA, TF-miRNA, TF-mRNA, TF-ncRNA and TF-miRNA-mRNA regulatory networks., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: ChIPBase (RRID:SCR_005404) Copy   

•   Source: SciCrunch Registry

http://gila.bioengr.uic.edu/snp/toposnp

A topographic database for analyzing non-synonymous SNPs (nsSNPs) that can be mapped onto known 3D structures of proteins. These include disease- associated nsSNPs derived from the Online Mendelian Inheritance in Man (OMIM) database and other nsSNPs derived from dbSNP, a resource at the National Center for Biotechnology Information that catalogs SNPs. TopoSNP further classifies each nsSNP site into three categories based on their geometric location: those located in a surface pocket or an interior void of the protein, those on a convex region or a shallow depressed region, and those that are completely buried in the interior of the protein structure. These unique geometric descriptions provide more detailed mapping of nsSNPs to protein structures. It also includes relative entropy of SNPs calculated from multiple sequence alignment as obtained from the Pfam database (a database of protein families and conserved protein motifs) as well as manually adjusted multiple alignments obtained from ClustalW. These structural and conservational data can be useful for studying whether nsSNPs in coding regions are likely to lead to phenotypic changes. TopoSNP includes an interactive structural visualization web interface, as well as downloadable batch data.

Proper citation: TopoSNP (RRID:SCR_005572) Copy   

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http://dommino.org

DOMMINO is a comprehensive structural database on macromolecular interactions. As of June, 2011, it contains more than 407,000 binary interactions. The distinctive features of DOMMINO are: # Automated updates: DOMMINO is fully automated and is designed to update itself on a weekly basis, one day after a PDB weekly update. Thus, the community will be able to study macromolecular interactions almost immediately after they are released by PDB. # Coverage of non-domain mediated interactions: In addition to domain-domain and domain-peptide interactions the database characterizes the interaction between domains and unstructured protein regions that are not parts of a domain, such as inter-domain linkers and N- and C-termini. The interactions that involve the latter unstructured parts of proteins have been included to the database for the first time providing additional ~186,000 interactions (~45% of the total number of interactions, as of June, 2011). # Coverage of new structural domains: DOMMINO employs one of the most accurate structural classifications of proteins, SCOP. In addition to the existing SCOP-annotated domains, we employ a state-of-the-art machine learning approach to classify newer protein structures into existing SCOP families. With the progress of structural genomics, we do not expect a significant growth of the number of structurally novel folds or protein families and therefore our method allows covering almost all new protein structures. In total, using this predictive approach has allowed us to add more than 261,000 new interactions, almost twice as many as existing SCOP-annotated interactions. # The web-interface is designed to give the user a possibility of a flexible search as well as the capability to study macromolecular interactions in a PDB structure at the interaction network level and at the individual interface level. The web interface of the DOMMINO database includes a comprehensive list of help topics linked to the specific actions. In addition, we have designed a step-by-step tutorial that covers all aspects of working with the data from DOMMINO using the web interface.

Proper citation: DOMMINO - Database Of MacroMolecular INteractiOns (RRID:SCR_005958) Copy   

•   Source: SciCrunch Registry

http://www.jcvi.org/charprotdb/index.cgi/home

The Characterized Protein Database, CharProtDB, is designed and being developed as a resource of expertly curated, experimentally characterized proteins described in published literature. For each protein record in CharProtDB, storage of several data types is supported. It includes functional annotation (several instances of protein names and gene symbols) taxonomic classification, literature links, specific Gene Ontology (GO) terms and GO evidence codes, EC (Enzyme Commisssion) and TC (Transport Classification) numbers and protein sequence. Additionally, each protein record is associated with cross links to all public accessions in major protein databases as ��synonymous accessions��. Each of the above data types can be linked to as many literature references as possible. Every CharProtDB entry requires minimum data types to be furnished. They are protein name, GO terms and supporting reference(s) associated to GO evidence codes. Annotating using the GO system is of importance for several reasons; the GO system captures defined concepts (the GO terms) with unique ids, which can be attached to specific genes and the three controlled vocabularies of the GO allow for the capture of much more annotation information than is traditionally captured in protein common names, including, for example, not just the function of the protein, but its location as well. GO evidence codes implemented in CharProtDB directly correlate with the GO consortium definitions of experimental codes. CharProtDB tools link characterization data from multiple input streams through synonymous accessions or direct sequence identity. CharProtDB can represent multiple characterizations of the same protein, with proper attribution and links to database sources. Users can use a variety of search terms including protein name, gene symbol, EC number, organism name, accessions or any text to search the database. Following the search, a display page lists all the proteins that match the search term. Click on the protein name to view more detailed annotated information for each protein. Additionally, each protein record can be annotated.

Proper citation: CharProtDB: Characterized Protein Database (RRID:SCR_005872) Copy   

•   Source: SciCrunch Registry

http://pbildb1.univ-lyon1.fr/virhostnet/

Public knowledge base specialized in the management and analysis of integrated virus-virus, virus-host and host-host interaction networks coupled to their functional annotations. It contains high quality and up-to-date information gathered and curated from public databases (VirusMint, Intact, HIV-1 database). It allows users to search by host gene, host/viral protein, gene ontology function, KEGG pathway, Interpro domain, and publication information. It also allows users to browse viral taxonomy.

Proper citation: VirHostNet: Virus-Host Network (RRID:SCR_005978) Copy   

•   Source: SciCrunch Registry

http://tbdb.org

Database providing integrated access to genome sequence, expression data and literature curation for Tuberculosis (TB) that houses genome assemblies for numerous strains of Mycobacterium tuberculosis (MTB) as well assemblies for over 20 strains related to MTB and useful for comparative analysis. TBDB stores pre- and post-publication gene-expression data from M. tuberculosis and its close relatives, including over 3000 MTB microarrays, 95 RT-PCR datasets, 2700 microarrays for human and mouse TB related experiments, and 260 arrays for Streptomyces coelicolor. (July 2010) To enable wide use of these data, TBDB provides a suite of tools for searching, browsing, analyzing, and downloading the data.

Proper citation: Tuberculosis Database (RRID:SCR_006619) Copy   

•   Source: SciCrunch Registry

http://www.droidb.org

A gene and protein interactions database designed specifically for the model organism Drosophila including protein-protein, transcription factor-gene, microRNA-gene, and genetic interactions. For advanced searches and dynamic graphing capabilities the IM Browser and a DroID Cytoscape plugin are available.

Proper citation: DroID - Drosophila Interactions Database (RRID:SCR_006634) Copy   

•   Source: SciCrunch Registry

http://prorepeat.bioinformatics.nl/

ProRepeat is an integrated curated repository and analysis platform for in-depth research on the biological characteristics of amino acid tandem repeats. ProRepeat collects repeats from all proteins included in the UniProt knowledgebase, together with 85 completely sequenced eukaryotic proteomes contained within the RefSeq collection. It contains non-redundant perfect tandem repeats, approximate tandem repeats and simple, low-complexity sequences, covering the majority of the amino acid tandem repeat patterns found in proteins. The ProRepeat web interface allows querying the repeat database using repeat characteristics like repeat unit and length, number of repetitions of the repeat unit and position of the repeat in the protein. Users can also search for repeats by the characteristics of repeat containing proteins, such as entry ID, protein description, sequence length, gene name and taxon. ProRepeat offers powerful analysis tools for finding biological interesting properties of repeats, such as the strong position bias of leucine repeats in the N-terminus of eukaryotic protein sequences, the differences of repeat abundance among proteomes, the functional classification of repeat containing proteins and GC content constrains of repeats' corresponding codons.

Proper citation: ProRepeat (RRID:SCR_006113) Copy   

•   Source: SciCrunch Registry

http://pcidb.russelllab.org/

The database of protein-chemical structural interactions includes all existing 3D structures of complexes of proteins with low molecular weight ligands. When one considers the proteins and chemical vertices of a graph, all these interactions form a network. Biological networks are powerful tools for predicting undocumented relationships between molecules. The underlying principle is that existing interactions between molecules can be used to predict new interactions. For pairs of proteins sharing a common ligand, we use protein and chemical superimpositions combined with fast structural compatibility screens to predict whether additional compounds bound by one protein would bind the other. The current version includes data from the Protein Data Bank as of August 2011. The database is updated monthly.

Proper citation: ProtChemSI (RRID:SCR_006115) Copy   

•   Source: SciCrunch Registry

http://prism.ccbb.ku.edu.tr/hotregion/index.php

Hot spots are energetically important residues at protein interfaces and they are not randomly distributed across the interface but rather clustered. These clustered hot spots form hot regions. Hot regions are important for the stability of protein complexes, as well as providing specificity to binding sites. HotRegion provides the hot region information of the interfaces by using predicted hot spot residues, and structural properties of these interface residues such as pair potentials of interface residues, accessible surface area (ASA) and relative ASA values of interface residues of both monomer and complex forms of proteins. Also, the 3D visualization of the interface and interactions among hot spot residues are provided. The number of interfaces in the database is 147909 and still growing.

Proper citation: HotRegion - A Database of Cooperative Hotspots (RRID:SCR_006022) Copy   

•   Source: SciCrunch Registry

http://biogps.org/

An extensible and customizable gene annotation portal that emphasizes community extensibility and user customizability. It is a complete resource for learning about gene and protein function. Community extensibility reflects a belief that any BioGPS user should be able to add new content to BioGPS using the simple plugin interface, completely independently of the core developer team. User customizability recognizes that not all users are interested in the same set of gene annotation data, so the gene report layouts enable each user to define the information that is most relevant to them. Currently, BioGPS supports eight species: Human (Homo sapiens), Mouse (Mus musculus), Rat (Rattus norvegicus), Fruitfly (Drosophila melanogaster), Nematode (Caenorhabditis elegans), Zebrafish (Danio rerio), Thale-cress (Arabidopsis thaliana), Frog (Xenopus tropicalis), and Pig (Sus scrofa). BioGPS presents data in an ortholog-centric format, which allows users to display mouse plugins next to human ones. Our data for defining orthologs comes from NCBI's HomoloGene database.

Proper citation: BioGPS: The Gene Portal Hub (RRID:SCR_006433) Copy   

•   Source: SciCrunch Registry

http://scansite.mit.edu/

Scansite searches for motifs within proteins that are likely to be phosphorylated by specific protein kinases or bind to domains such as SH2 domains, 14-3-3 domains or PDZ domains. The Motifscanner program utilizes an entropy approach that assesses the probability of a site matching the motif using the selectivity values and sums the logs of the probability values for each amino acid in the candidate sequence. The program then indicates the percentile ranking of the candidate motif in respect to all potential motifs in proteins of a protein database. When available, percentile scores of some confirmed phosphorylation sites for the kinase of interests or confirmed binding sites of the domain of interest are provided for comparison with the scores of the candidate motifs.

Proper citation: Scansite (RRID:SCR_007026) Copy   

•   Source: SciCrunch Registry

http://www.iiserpune.ac.in/~coee/histome/

Database of human histone variants, sites of their post-translational modifications and various histone modifying enzymes. The database covers 5 types of histones, 8 types of their post-translational modifications and 13 classes of modifying enzymes. Many data fields are hyperlinked to other databases (e.g. UnprotKB/Swiss-Prot, HGNC, OMIM, Unigene etc.). Additionally, this database also provides sequences of promoter regions (-700 TSS +300) for all gene entries. These sequences were extracted from the UCSC genome browser. Sites of post-translational modifications of histones were manually searched from PubMed listed literature. Current version contains information for about ~50 histone proteins and ~150 histone modifying enzymes. HIstome is a combined effort of researchers from two institutions, Advanced Center for Treatment, Research and Education in Cancer (ACTREC), Navi Mumbai and Center of Excellence in Epigenetics (CoEE), Indian Institute of Science Education and Research (IISER), Pune.

Proper citation: HIstome: The Histone Infobase (RRID:SCR_006972) Copy   

•   Source: SciCrunch Registry

http://www.hprd.org

Database that represents a centralized platform to visually depict and integrate information pertaining to domain architecture, post-translational modifications, interaction networks and disease association for each protein in the human proteome. All the information in HPRD has been manually extracted from the literature by expert biologists who read, interpret and analyze the published data.

Proper citation: HPRD - Human Protein Reference Database (RRID:SCR_007027) Copy   

•   Source: SciCrunch Registry

http://xin.cz3.nus.edu.sg/group/cjttd/ttd.asp

A database to provide information about the known and explored therapeutic protein and nucleic acid targets, the targeted disease, pathway information and the corresponding drugs/ligands directed at each of these targets. Also included in this database are links to relevant databases that contain information about the function, sequence, 3D structure, ligand binding properties, enzyme nomenclature and related literatures of each target.This database currently contains 1535 targets and 2107 drugs/ligands. Queries can be submitted by entering or selecting the required information in any one or combination of the five fields in the form. User can specify full name or any part of the name in a text field, or choose one item from an selection field.

Proper citation: Therapeutic Target Database (RRID:SCR_006892) Copy   

•   Source: SciCrunch Registry

http://www.molecularconnections.com/home/en/home/products/netPro

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 1, 2023. Comprehensive database of Protein-Protein and Protein-Small molecules interaction, consisting of more than 320,000 interactions captured from more than 1500 abstracts, approximately 1600 published journals and more than 60,000 references. The strength of NetPro lies in the complete manual curation of literature. It covers several entities other than proteins as interacting partners, like RNA, DNA, processes, etc. with well defined, exhaustive interaction terms. NetPro has received several accolades for the quality and quantity of data it contains. It has become an important resource for target identification, validation and pathway research and has subscribers from all over the globe including 3 of the top 5 pharmas.

Proper citation: Molecular Connections NetPro (RRID:SCR_000395) Copy   

•   Source: SciCrunch Registry

http://psychiatry.igm.jhmi.edu/SynaptomeDB/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Ontology-based knowledgebase for synaptic genes. These genes encode components of the synapse including neurotransmitters and their receptors, adhesion / cytoskeletal proteins, scaffold proteins, transporters, and others. It integrates various and complex data sources for synaptic genes and proteins., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: SynaptomeDB (RRID:SCR_000157) Copy   

•   Source: SciCrunch Registry

http://www.bindingdb.org

Web accessible database of data extracted from scientific literature, focusing on proteins that are drug-targets or candidate drug-targets and for which structural data are present in Protein Data Bank . Website supports query types including searches by chemical structure, substructure and similarity, protein sequence, ligand and protein names, affinity ranges and molecular weight . Data sets generated by BindingDB queries can be downloaded in form of annotated SDfiles for further analysis, or used as basis for virtual screening of compound database uploaded by user. Data are linked to structural data in PDB via PDB IDs and chemical and sequence searches, and to literature in PubMed via PubMed IDs .

Proper citation: BindingDB (RRID:SCR_000390) Copy   

•   Source: SciCrunch Registry

http://text0.mib.man.ac.uk/software/mldic/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 9, 2022. System that retrieves relevant UniProt IDs from BioThesaurus entries using a soft string matching algorithm.

Proper citation: Smart Dictionary Lookup (RRID:SCR_000568) Copy   

•   Source: SciCrunch Registry