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http://www.wwpdb.org/

Public global Protein Data Bank archive of macromolecular structural data overseen by organizations that act as deposition, data processing and distribution centers for PDB data. Members are: RCSB PDB (USA), PDBe (Europe) and PDBj (Japan), and BMRB (USA). This site provides information about services provided by individual member organizations and about projects undertaken by wwPDB. Data available via websites of its member organizations.

Proper citation: Worldwide Protein Data Bank (wwPDB) (RRID:SCR_006555) Copy   

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https://www.ncbi.nlm.nih.gov/geo/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on January 19, 2022.

Proper citation: NCBI Epigenomics (RRID:SCR_006151) Copy   

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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   

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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   

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http://www.physionet.org/physiobank/database/gaitndd/

Database of records from patients with Parkinson's disease (n = 15), Huntington's disease (n = 20), or amyotrophic lateral sclerosis (n = 13). Records from 16 healthy control subjects are also included here. The raw data were obtained using force-sensitive resistors, with the output roughly proportional to the force under the foot. Stride-to-stride measures of footfall contact times were derived from these signals.

Proper citation: Gait Dynamics in Neuro-Degenerative Disease Data Base (RRID:SCR_006979) Copy   

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http://ekhidna.biocenter.helsinki.fi/dali/start

Resource out of service. Documented on May, 5th, 2021.The Dali Database is based on all-against-all 3D structure comparison of protein structures in the Protein Data Bank (PDB). The structural neighborhoods and alignments are automatically maintained and regularly updated using the Dali search engine. The Dali Database contains structural alignments of PDB90 versus the full PDB using DaliLite. The data can be viewed interactively here, or downloaded in its entirety Users may search by PDB identifier or keyword.

Proper citation: Dali database (RRID:SCR_006974) Copy   

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http://zork.wustl.edu/nida/neurosnp.html

The goal of this project is to aid genetic association studies of addiction by creating a resource of biologically relevant genes, pathways and single nucleotide polymorphisms (SNPs). The primary users of the NeuroSNP resource are investigators conducting genome-wide association studies (GWASs) of addiction-related phenotypes. NeuroSNP will allow investigators to identify biologically relevant genes for addiction based on curated expert knowledge, and assess the coverage of these genes provided by commercial SNP microarrays. If investigators wish to ensure the coverage of certain addiction-related genes is optimal, NeuroSNP provides a mechanism for supplementation. While commercial SNP microarrays offer affordable and comprehensive coverage of the human genome, some diseases have biologically relevant genomic regions that may require additional coverage. Addiction, for example, is believed to be influenced by complex interactions involving several genes and pathways. NIDA has assembled a number of investigators specializing in fields such as genetics, pharmacogenetics, bioinformatics and neurobiology through a Request for Information. These investigators have pooled their expert knowledge to produce a database of addiction-related genes and SNPs. Commercial SNP microarrays, such as those offered by Affymetrix and Illumina, are then analyzed to determine how well certain addiction-related genes are covered. When the coverage is less than optimal, a SNP prioritization scheme is used to supplement the commercial array with the most biologically informative markers. For example, SNPs in coding regions, promoters, and evolutionary conserved regions are selected first.

Proper citation: NeuroSNP Project (RRID:SCR_007029) Copy   

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https://sites.google.com/site/bipolardatabase/

Database of 141 studies which have investigated brain structure (using MRI and CT scans) in patients with bipolar disorder compared to a control group. Ninety-eight studies and 47 brain structures are included in the meta-analysis. The database and meta-analysis are contained in an Excel spreadsheet file which may be freely downloaded from this website.

Proper citation: Bipolar Disorder Neuroimaging Database (RRID:SCR_007025) Copy   

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http://www.genome.ad.jp/ligand/

KEGG LIGAND contains knowledge of chemical substances and reactions that are relevant to life. It is a composite database consisting of COMPOUND, GLYCAN, REACTION, RPAIR, and ENZYME databases, whose entries are identified by C, G, R, RP, and EC numbers, respectively. ENZYME is derived from the IUBMB/IUPAC Enzyme Nomenclature, but the others are internally developed and maintained. The primary database of KEGG LIGAND is a relational database with the KegDraw interface, which is used to generated the secondary (flat file) database for DBGET.

Proper citation: Database of Chemical Compounds and Reactions in Biological Pathways (RRID:SCR_006851) Copy   

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

Database (anonymous FTP) resulting from a collaborative effort to identify a core set of human and mouse protein coding regions that are consistently annotated and of high quality. The long term goal is to support convergence towards a standard set of gene annotations. Collaborators are EBI, NCBI, UCSC, WTSI and the initial results are also available from the participants'''' genome browser Web sites. In addition, CCDS identifiers are indicated on the relevant NCBI RefSeq and Entrez Gene records and in Map Viewer displays of RNA (RefSeq) and Gene annotations on the reference assembly.

Proper citation: Consensus CDS (RRID:SCR_006729) Copy   

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http://cbl-gorilla.cs.technion.ac.il/

A tool for identifying and visualizing enriched GO terms in ranked lists of genes. It can be run in one of two modes: * Searching for enriched GO terms that appear densely at the top of a ranked list of genes or * Searching for enriched GO terms in a target list of genes compared to a background list of genes.

Proper citation: GOrilla: Gene Ontology Enrichment Analysis and Visualization Tool (RRID:SCR_006848) Copy   

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http://tmbeta-genome.cbrc.jp/TMFunction/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 29,2025. Database of functional residues in alpha-helical and beta-barrel membrane proteins. Each protein is identified with its name and source alongwith the Uniprot code. The protein data bank (PDB) codes are also given for available proteins. Different methods and experimental parameters, for example, affinity, dissociation constant, IC50, activity etc. are given in the database. Further, the database provides the numerical experimental value for each residue (or mutant) in a protein. The experimental data are collected from the literature both by searching the journals as well as with the keyword search at PUBMED. In addition, complete reference is given with journal citation and PMID number. TNFunction is cross-linked with the sequence database, Uniprot, structural database, PDB, and literature database, PubMed. The WWW interface enables users to search data based on various terms with different display options for outputs.

Proper citation: TM Function Database (RRID:SCR_007058) Copy   

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http://haldanessieve.org/

Blog discussing preprints in population and evolutionary genetics.

Proper citation: Haldanes Sieve (RRID:SCR_007178) Copy   

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

A database of interactions between HIV-1 and human proteins published in the peer-reviewed literature. The goal is to provide a concise, yet detailed, summary of all known interactions of HIV-1 proteins with host cell proteins, other HIV-1 proteins, or proteins from disease organisms associated with HIV/AIDS. For each HIV-1 human protein interaction the following information is provided: * NCBI Reference Sequence (RefSeq) protein accession numbers. * NCBI Entrez Gene ID numbers. * Amino acids from each protein that are known to be involved in the interaction. * Brief description of the protein-protein interaction. * Keywords to support searching for interactions. * PubMed identification numbers (PMIDs) for all journal articles describing the interaction. In addition, all protein-protein interactions documented in the database are integrated into Entrez Gene records and listed in the ''HIV-1 protein interactions'' section of Entrez Gene reports. The database is also tightly linked to other databases through Entrez Gene, enabling users to search for an abundance of information related to HIV pathogenesis and replication.

Proper citation: HIV-1 Human Protein Interaction Database (RRID:SCR_006879) Copy   

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http://blogs.discovermagazine.com/loom/

The Loom is a blog about life, past and future. Written by DISCOVER contributing editor and columnist Carl Zimmer. Carl Zimmer writes about science regularly for the New York Times and magazines such as Discover, where he is a contributing editor and columnist.

Proper citation: The Loom (RRID:SCR_006877) Copy   

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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   

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http://www.genome.ad.jp/aaindex/

AAindex is a database of numerical indices representing various physicochemical and biochemical properties of amino acids and pairs of amino acids. AAindex consists of three sections now: AAindex1 for the amino acid index of 20 numerical values, AAindex2 for the amino acid mutation matrix and AAindex3 for the statistical protein contact potentials. All data are derived from published literature. An amino acid index is a set of 20 numerical values representing any of the different physicochemical and biological properties of amino acids. The AAindex1 section of the Amino Acid Index Database is a collection of published indices together with the result of cluster analysis using the correlation coefficient as the distance between two indices. This section currently contains 544 indices. Another important feature of amino acids that can be represented numerically is the similarity between amino acids. Thus, a similarity matrix, also called a mutation matrix, is a set of 210 numerical values, 20 diagonal and 20x19/2 off-diagonal elements, used for sequence alignments and similarity searches. The AAindex2 section of the Amino Acid Index Database is a collection of published amino acid mutation matrices together with the result of cluster analysis. This section currently contains 94 matrices. In the release 9.0, we added a collection of published protein pairwise contact potentials to AAindex as AAindex3. This section currently contains 47 contact potential matrices. Sponsors: This work was supported by grants and resources from the Ministry of Education, Culture, Sports, Science and Technology, and the Japan Science and Technology Agency, and the Bioinformatics Center, Institute for Chemical Research, Kyoto University and the Super Computer System, Human Genome Center, Institute of Medical Science, University of Tokyo.

Proper citation: Amino Acid Index Database (RRID:SCR_007044) Copy   

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http://unitrap.cbm.fvg.it/

A curated collection of all the trapped ES cell clones. Gene-trapping is a valuable tool that uses random mutagenesis to create hypomorphic or null alleles by insertion of exogenous DNA. Since numerous public and private projects have been performing gene trapping over the last few years,it is natural that large overlaps exist and some vectors produce better knock-outs than others due to their insertion site. Considering the high need to develop a comprehensive database that would include both public and private data to provide public access to this essential biological resource, we developed UniTrap, a curated collection of all the trapped ES cell clones, collected from public and private databases. We have developed a bioinformatics pipeline to automate the identification and characterization of trapped genes starting from their transcriptional sequence tags.We process gene trap sequence tags from ES cell clones to generate ‘UniTraps’, i.e. distinct collections of unambiguous insertions at the same subgenic region of annotated genes (RefSeq and Ensembl genes). The UniTrap resource contains data relative to well-known trapped genes. We aim to provide the wet lab researchers with a comprehensive, regularly updated database and curated tools for(i) identifying and comparing the clones carrying a trap into the genes of interest,(ii) evaluating the severity of the mutation to the protein function in each independent trapping event, and(iii) supplying complete information to perform PCR, RT-PCR and restriction experiments to verify the clone and identify the exact point of vector insertion.

Proper citation: UniTrap (RRID:SCR_007046) Copy   

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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   

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http://www.signaling-gateway.org/molecule/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 29,2025. Relational database of all significant published qualitative and quantitative information on cell signaling proteins. The Molecule Pages database was developed with the specific aim of allowing interactions, and indeed whole pathways, to be modeled. The goal is to filter the data to present only validated information. In addition, the Gateway is the home of Signaling Update, which provides a one-stop overview of the latest and hottest research in cell signaling for both the specialist and non-specialist alike.

Proper citation: UCSD-Nature Signaling Gateway Molecule Pages (RRID:SCR_006907) Copy   

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