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http://ptmcode.embl.de/

Database of known and predicted functional associations between protein posttranslational modifications (PTMs) within proteins. In its first release it contains 13 different PTM types. PTM types are abbreviated in a two letter code as: Ph (phosphorylation), NG (N-linked glycosylation), Ac (acetylation), OG (O-linked glycosylation), Ub (ubiquitination), Me (methylation), SM (SUMOylation), Hy (hydroxylation), Ca (carboxylation), Pa (palmitoylation), Su (sulfation), Ni (nitrosylation) and CG (C-linked glycosylation). These PTMs are present in 25,765 proteins of 8 different eukaryotes. The database is focused on the exploration of the global post-translational regulation of proteins, not only by describing the set of its modifications, but by identifying the functional associations among the PTMs present in the protein. To do that, they combine five different evidence channels based on a literature survey, the modified residue co-evolution, their structural proximity, their competition for the same residue and the location within PTM highly-enriched protein regions (hotspots) and show the functional associations within the context of the protein architecture.

Proper citation: PTMcode (RRID:SCR_002046) Copy   

•   Source: SciCrunch Registry

http://bmerc.bu.edu/projects/wdrepeat/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 26, 2016. This website contains a library of WD-repeat containing proteins in which the repeats appear as multi-aligned sets. WD-repeat-containing proteins are those that contain 4 or more copies of the WD-repeat (tryptophan-aspartate repeat), a sequence motif approximately 31 amino acids long, that encodes a structural repeat. This repeat is described by the following profile, where x is ANY amino acid. By clicking on each high-lighted character you will obtain the distribution of amino acids found at that position of the repeat among an aligned set of WD-repeat containing proteins. The tertiary structure of only one member of this family has been determined, that of the G protein beta subunit, which contains 7 WD-repeats. Each of the 7 repeats folds into a small antiparallel beta-sheet. The over-lines above indicate the position of these strands, with a being the strand closest to the central pore and d at the external surface of the folded protein. These sheets are arranged around a central pseudosymmetry axis into a beta propeller. The WD-repeat-containing proteins form a very large family that is diverse in both its function and domain structure. Within all these proteins the WD-repeat domains are thought to have two common features: the domain folds into a beta propeller; and the domains form a platform without any catalytic activity on which multiple protein complexes assemble reversibly. The fact that these proteins play such key roles in the formation of protein-protein complexes in nearly all the major pathways and organelles unique to eukaryotic cells has two important implications. It supports both their ancient and proto eukaryotic origins and supports a likely association with many genetic diseases.

Proper citation: WD repeat Family of Proteins (RRID:SCR_002160) Copy   

•   Source: SciCrunch Registry

http://cbrc.kaust.edu.sa/tcof/

Database that facilitates the exploration of proteins involved in the regulation of transcription in humans by binding to regulatory DNA regions (transcription factors) and proteins involved in the regulation of transcription in humans by interacting with transcription factors and not binding to regulatory DNA regions (transcription co-factors).

Proper citation: TcoF (RRID:SCR_002158) Copy   

•   Source: SciCrunch Registry

https://cell-innovation.nig.ac.jp/GNP/index_e.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Integrated database of experiment data generated by participating research institutes and public databases relating to: 1) transcription starting position of human genes in the human genome, 2) conjunction to control region on transcriptional factors and the human genome 3) protein-protein interaction with a central focus on transcription factors organized for use in genome level research. Gene Search is the function to search the integrated database by using keywords and public IDs. The search results can be visualized by: * Genome Explorer : provides annotation of landmarks (genes, transcription start sites, etc.) aligned in accordance with their genome locations. * PPI Network : provides a graphical view of protein-protein interaction (PPI) network from the experimental data generated under the project and the public datasets. * Expression Profile : clusters genes by expression pattern and display the result with heatmap. The function provides genes which have relation of coregulation and anti-coregulation. * Comparison Viewer : This function gives the view to compare the genomic regions between human and mouse homologous genes. The viewer shows the distribution of transcription start sites (TSS) as the way of separable by tissues or time points with other landmarks on genome region. * Gene Stock : This is the function to save the gene list that you are interested until the session is closed.

Proper citation: Genome Network Platform (RRID:SCR_001737) Copy   

•   Source: SciCrunch Registry

http://srv00.recas.ba.infn.it/ASPicDB/

A database to access reliable annotations of the alternative splicing pattern of human genes, obtained by ASPic algorithm (Castrignano et al. 2006), and to the functional annotation of predicted isoforms. Users may select and extract specific sets of data related to genes, transcripts and introns fulfilling a combination of user-defined criteria. Several tabular and graphical views of the results are presented, providing a comprehensive assessment of the functional implication of alternative splicing in the gene set under investigation. ASPicDB also includes information on tissue-specific splicing patterns of normal and cancer cells, based on available EST data and their library source annotation.

Proper citation: ASPicDB (RRID:SCR_002102) Copy   

•   Source: SciCrunch Registry

http://services.bio.ifi.lmu.de:1046/AutoPSIDB/

Searchable database for predicted protein sequences and structures. It has the ability to search through PDB ID, UniProt ID, and descriptive classifiers.

Proper citation: AutoPSI database of predicted SCOP classifications (RRID:SCR_001923) Copy   

•   Source: SciCrunch Registry

http://netbio.bgu.ac.il/tissuenet/

Database of human tissue protein-protein interactions (PPIs) that associates each interaction with human tissues that express both pair mates. This was achieved by integrating current data of experimentally detected PPIs with extensive data of gene and protein expression across 16 main human tissues. Users can query TissueNet using a protein and retrieve its PPI partners per tissue, or using a PPI and retrieve the tissues expressing both pair mates. The graphical representation of the output highlights tissue-specific and tissue-wide PPIs. Thus, TissueNet provides a unique platform for assessing the roles of human proteins and their interactions across tissues.

Proper citation: TissueNet - The Database of Human Tissue Protein-Protein Interactions (RRID:SCR_002052) Copy   

•   Source: SciCrunch Registry

http://irefindex.org

An index of protein interactions available in a number of primary interaction databases including BIND, BioGRID, CORUM, DIP, HPRD, IntAct, MINT, MPact, MPPI and OPHID. This index includes multiple interaction types including physical and genetic (mapped to their corresponding protein products) as determined by a multitude of methods. This index allows the user to search for a protein and retrieve a non-redundant list of interactors for that protein. iRefIndex uses the Sequence Global Unique Identifier (SEGUID) to group proteins and interactions into redundant groups. This method allows users to integrate their own data with the iRefIndex in a way that ensures proteins with the exact same sequence will be represented only once. iRefIndex project has three long term objectives: # to facilitate exchange of interaction data between interaction databases. # to consolidate interaction data from multiple sources. # to provide feedback to source interaction databases. iRefIndex is made available in a number of formats: MITAB tab-delimited text files, iRefWeb interface, iRefScape plugin for Cytoscape, PSICQUIC Web services, and an interface for the R programming language environment.

Proper citation: Interaction Reference Index (RRID:SCR_002085) Copy   

•   Source: SciCrunch Registry

http://srv00.recas.ba.infn.it/SpliceAidF/search.php

A database of human splicing factors and their RNA - binding sites. For each splicing factor (SF) the database reports its functional domains and its protein and chemical interactors. Furthermore, experimentally validated RNA-SF interactions are collected, including relevant information on the RNA binding sites such as the genes where these sites lie, their genomic coordinates, the splicing effects, experimental procedures, as well as the corresponding bibliographic references. Information from experiments showing no RNA-SF binding is also collected, at least in the assayed conditions. SpliceAid-F contains 4227 interactions, 2622 RNA binding sites and 1170 no-binding sites, including information on binding and no-binding specificity in different cellular contexts. SpliceAid-F can provide significant information to explain an observed splicing pattern as well as the effect of mutations in functional regulatory elements.

Proper citation: SpliceAid-F (RRID:SCR_002082) Copy   

•   Source: SciCrunch Registry

http://prism.ccbb.ku.edu.tr/prism/

It is a web-server that can be used to explore protein interfaces and predict protein-protein interactions. It is a website for protein interface analysis and prediction of putative protein-protein interactions. It is composed of a database holding protein interface structures derived from the Protein Data Bank (PDB). The server also includes summary information about related proteins and an interactive protein interface viewer. A list of putative protein-protein interactions obtained by running our prediction algorithm can also be accessed. These results are applied to a set of protein structures obtained from the PDB at the time of algorithm execution. Users can browse through the non-redundant dataset of representative interfaces on which the prediction algorithm depends, retrieve the list of similar structures to these interfaces or see the results of interaction predictions for a particular protein. Another service provided is interactive prediction. This is done by running the algorithm for user input structures.

Proper citation: Protein Interactions by Structural Matching (RRID:SCR_002116) Copy   

•   Source: SciCrunch Registry

http://hupi.ircm.qc.ca/hupi/

The Human Proteotheque Initiative is a multidisciplinary project aimed at building a repertoire of comprehensive maps of human protein interaction networks. The information contained in the Proteotheque is made publicly available through an interactive web site that can be consulted to visualize some of the fundamental molecular connections formed in human cells and to determine putative functions of previously uncharacterized proteins based on guilt by association. The process governing the evolution of HuPI towards becoming a repository of accurate and complete protein interaction maps is described.

Proper citation: Database of the Human Proteotheque Initiative (RRID:SCR_002076) Copy   

•   Source: SciCrunch Registry

http://www.jcvi.org/mpidb

Database that collects and provides all known physical microbial interactions. Currently, 24,295 experimentally determined interactions among proteins of 250 bacterial species/strains can be browsed and downloaded. These microbial interactions have been manually curated from the literature or imported from other databases (IntAct, DIP, BIND, MINT) and are linked to 26,578 experimental evidences (PubMed ID, PSI-MI methods). In contrast to these databases, interactions in MPIDB are further supported by 68,346 additional evidences based on interaction conservation, co-purification, and 3D domain contacts (iPfam, 3did). (spoke/matrix) binary interactions inferred from pull-down experiments are not included.

Proper citation: MPIDB (RRID:SCR_001898) Copy   

•   Source: SciCrunch Registry

http://www.bacteriome.org

Database integrating physical (protein-protein) and functional interactions within the context of an E. coli knowledgebase. Presently the resource offers access to two types of network: * A network of functional interactions derived through exploiting available functional genomic datasets within a Bayesian framework * Two networks of experimentally derived protein-protein interactions - a "core" network consisting of interactions deemed to be of "high quality"; and an "extended" network which extends the "core" network by including interactions for which experimental evidence is less strong.

Proper citation: Bacteriome.org (RRID:SCR_001934) Copy   

•   Source: SciCrunch Registry

http://kinase.bioinformatics.tw/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. A comprehensive human kinase interactome and phospho-protein database. PhosphoPOINT also annotates any amino acids near the phosphorylation sites where a cSNP may cause a phosphorylation site to be lost, and at the same time identifies how such alteration of the phosphorylation site may lead to human disease. PhosphoPOINT integrates 4,195 phospho-proteins, 518 serine/threonine/tyrosine kinases, and their corresponding PPI datasets with the goal of delineating the interactions among kinases, their potential substrates and their interacting (phospho)-proteins. PhosphoPOINT has integrated human protein kinases, phospho-proteins, and PPI datasets with the goal to delineate four kinds of links among kinases. These include their interacting proteins, substrates, and substrates as well as interacting phospho-proteins. Some of these interacting proteins for kinases are phospho-proteins, which might have the potential to serve as substrates for the interacting kinases.

Proper citation: PhosphoPOINT (RRID:SCR_002109) Copy   

•   Source: SciCrunch Registry

http://www.cbil.upenn.edu/ParaDBs/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 28,2025. These databases were constructed by extracting the organism specific ESTs from dbEST, removing polyA sequences from the ends and trimming 5' and 3' regions with greater than 25% N's in a 20 base pair window. These quality sequences were then aligned using the cap2 program and the consensus sequences thus generated put into a database that is available on the web. A number of parasitic organisms were chosen that have between 3000 and 15000 ESTs. The attempt here is to provide useful information and analyses to the scientific community without curating the results in any way. A total of 55192 ESTs, deposited into dbEST/GenBank, were included in the analyses. The resulting sequences have been clustered into nonredundant gene assemblies and deposited into a relational database that supports a variety of sequence and text searches. This database has been used to compare the gene assemblies using BLAST similarity comparisons to the public protein databases to identify putative genes. Of these new entries, approximately 15%-20% represent putative homologs with a conservative cutoff of p < 10(-9), thus identifying many conserved genes that are likely to share common functions with other well-studied organisms. Gene assemblies were also used to identify strain polymorphisms, examine stage-specific expression, and identify gene families. An interesting class of genes that are confined to members of this phylum and not shared by plants, animals, or fungi, was identified. These genes likely mediate the novel biological features of members of the Apicomplexa and hence offer great potential for biological investigation and as possible therapeutic targets.

Proper citation: Parasite Databases of Clustered ESTs (RRID:SCR_002262) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/compneur-srv/LGICdb/

Database providing access to information about transmembrane proteins that exist under different conformations, with three primary subfamilies: the cys-loop superfamily, the ATP gated channels superfamily, and the glutamate activated cationic channels superfamily. Due to the lack of evolutionary relationship, these three superfamilies are treated separately. It currently contains 554 entries of ligand-activated ion channel subunits. In this database one may find: the nucleic and proteic sequences of the subunits. Multiple sequence alignments can be generated, and some phylogenetic studies of the superfamilies are provided. Additionally, the atomic coordinates of subunits, or portion of subunits, are provided when available. Redundancy is kept to a minimum, i.e. one entry per gene. Each entry in the database has been manually constructed and checked by a researcher of the field in order to reduce the inaccuracies to a minimum. NOTE: This database is not actively maintained anymore. People should not consider it as an up-to-date trustable resource. For any new work, they should consider using alternative sources, such as UniProt, Ensembl, Protein Databank etc.

Proper citation: Ligand-Gated Ion Channel Database (RRID:SCR_002418) Copy   

•   Source: SciCrunch Registry

http://mips.helmholtz-muenchen.de/genre/proj/corum

Database of manually annotated protein complexes from mammalian organisms. Annotation includes protein complex function, localization, subunit composition, literature references and more. All information is obtained from individual experiments published in scientific articles, but data from high-throughput experiments is excluded.
The majority of protein complexes in CORUM originates from man (65%), followed by mouse (14%) and rat (14%)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: CORUM (RRID:SCR_002254) Copy   

•   Source: SciCrunch Registry

http://www.hiv.lanl.gov/content/immunology/index

An annotated, searchable collection of HIV-1 cytotoxic and helper T-cell epitopes and antibody binding sites, plus related tools and information. The goal of this database is to provide a comprehensive listing of defined HIV epitopes. These data are also printed in the HIV Molecular Immunology compendium, which is updated yearly and provided free of charge to scientific researchers, both by online download and as a printed copy. The data included in this database are extracted from the HIV immunology literature. HIV-specific B-cell and T-cell responses are summarized and annotated. Immunological responses are divided into three sections, CTL (CD8+), T helper (CD4+), and antibody. Within these sections, defined epitopes are organized by protein and binding sites within each protein, moving from left to right through the coding regions spanning the HIV genome. We include human responses to natural HIV infections, as well as vaccine studies in a range of animal models and human trials. Responses that are not specifically defined, such as responses to whole proteins or monoclonal antibody responses to discontinuous epitopes, are summarized at the end of each protein sub-section. Studies describing general HIV responses to the virus, but not to any specific protein, are included at the end of each section. The annotation includes information such as cross-reactivity, escape mutations, antibody sequence, TCR usage, functional domains that overlap with an epitope, immune response associations with rates of progression and therapy, and how specific epitopes were experimentally defined. Basic information such as HLA specificities for T-cell epitopes, isotypes of monoclonal antibodies, and epitope sequences are included whenever possible. All studies that we can find that incorporate the use of a specific monoclonal antibody are included in the entry for that antibody. A single T-cell epitope can have multiple entries, generally one entry per study. Finally, tables and maps of all defined linear epitopes relative to the HXB2 reference proteins are provided. Alignments of CTL, helper T-cell, and antibody epitopes are available through the search interfaces. Only responses to HIV-1 and HIV-2 are included in the database.

Proper citation: HIV Molecular Immunology Database (RRID:SCR_002893) Copy   

•   Source: SciCrunch Registry

http://karg.cbi.pku.edu.cn

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 14,2026. Database of data and knowledge linking genes and chromosome regions to addiction that were extracted from reviewing more than 1,000 peer-reviewed publications from between 1976 and 2006. This list of publications included review papers on addiction selected from results of PUBMED query "(addiction OR drug abuse) AND review" as well as research papers selected from PUBMED query "(addiction OR drug abuse) AND (gene OR microarray OR proteomics OR QTL OR population association OR genetic linkage)". The data spanned multiple technology platforms including classical hypothesis-testing of single genes, identification of significantly differentially expressed genes in microarray experiments, identification of significantly differentially expressed proteins in proteomics assays, identification of addiction-vulnerable chromosome regions in animal QTL studies, genetic linkage studies, population association studies, and OMIM annotations. From each publication they collected the genes, proteins, or chromosome regions linked to addiction, as well as metadata such as species, nature of the addictive substance, studied brain regions, technology platforms, and experimental parameters. In total, they collected 2,343 items of evidence linking 1,500 human genes to addiction. Among them 396 genes were supported by two or more items of evidence. The interface supports browsing of the genes by chromosome or pathways, advanced text search by gene ID, organism, type of addictive substance, technology platform, protein domain, and/or PUBMED ID, and sequence search by BLAST similarity. All data, database schema, and MySQL commands are freely available for download.

Proper citation: Knowledgebase for Addiction Related Genes (RRID:SCR_002687) Copy   

•   Source: SciCrunch Registry

http://ecogene.org/

Database that contains updated information about the Escherichia coli K-12 genome and proteome sequences, including extensive gene bibliographies. Users are able to download customized tables, perform Boolean query comparisons, generate sets of paired DNA sequences, and download any E. coli K-12 genomic DNA sub-sequence. BLAST functions, microarray data, an alphabetical index of genes, and gene overlap queries are also available. The Database Table Downloads Page provides a full list of EG numbers cross-referenced to the new cross-database ECK numbers and other common accession numbers, as well as gene names and synonyms. Monthly release archival downloads are available, but the live, daily updated version of EcoGene is the default mysql database for download queries.

Proper citation: EcoGene (RRID:SCR_002437) Copy   

•   Source: SciCrunch Registry