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http://gene3d.biochem.ucl.ac.uk/Gene3D/

A large database of CATH protein domain assignments for ENSEMBL genomes and Uniprot sequences. Gene3D is a resource of form studying proteins and the component domains. Gene3D takes CATH domains from Protein Databank (PDB) structures and assigns them to the millions of protein sequences with no PDB structures using Hidden Markov models. Assigning a CATH superfamily to a region of a protein sequence gives information on the gross 3D structure of that region of the protein. CATH superfamilies have a limited set of functions and so the domain assignment provides some functional insights. Furthermore most proteins have several different domains in a specific order, so looking for proteins with a similar domain organization provides further functional insights. Strict confidence cut-offs are used to ensure the reliability of the domain assignments. Gene3D imports functional information from sources such as UNIPROT, and KEGG. They also import experimental datasets on request to help researchers integrate there data with the corpus of the literature. The website allows users to view descriptions for both single proteins and genes and large protein sets, such as superfamilies or genomes. Subsets can then be selected for detailed investigation or associated functions and interactions can be used to expand explorations to new proteins. The Gene3D web services provide programmatic access to the CATH-Gene3D annotation resources and in-house software tools. These services include Gene3DScan for identifying structural domains within protein sequences, access to pre-calculated annotations for the major sequence databases, and linked functional annotation from UniProt, GO and KEGG., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Gene3D (RRID:SCR_007672) Copy   

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http://www.glycosciences.de/modeling/glycomapsdb/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 15,2026. A data base system for the management of conformational maps and profiles, the system allows conformational maps to be archived in a standard format, and it provides search and comparison facilities. An interface to structures from Sweet-DB is implemented. GlycoMapsDB also offers scientists the possibility of adding their own publicized structures to the database via a web interface. GlycoMapsDB provides maps of 3D and 2D mono- and disaccharides. It provides users conformational information on carbohydrates and glycoproteins.

Proper citation: GlycoMapsDB (RRID:SCR_002810) Copy   

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http://genome.jgi.doe.gov/programs/fungi/index.jsf

Fungal genomics database and interactive analytical tools that integrates all fungal genomes for diverse fungi that are important for energy and environment, the focus of the JGI Fungal program. It integrates genomics data from the DOE JGI and its users and promotes user community participation in data submission, annotation and analysis. Over 100 newly sequenced and annotated fungal genomes from JGI and elsewhere are available to the public through MycoCosm, and new annotated genomes are being added to this resource upon completion of annotation. MycoCosm offers web-based genome analysis tools for fungal biologists to ''navigate'' through sequenced genomes and explore them in the context of ''genome-centric'' and ''comparative views''.

Proper citation: MycoCosm (RRID:SCR_005312) Copy   

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http://hivdb.stanford.edu/

The Stanford University HIV Drug Resistance Database is a curated public database designed to represent, store, and analyze the different forms of data underlying HIVs drug resistance. HIVDB has three main types of content: (1) Database queries and references, (2) Interactive programs, and (3) Educational resources. Database queries are designed primarily for researchers studying HIV drug resistance. The interactive programs and educational resources are designed for both researchers and those wishing to learn more about HIV drug resistance. 1.DATABASE QUERY AND REFERENCE PAGES Genotype-Treatment Correlations This Genotype-Treatment section of the database links to 15 interactive query pages that explore the relationship between treatment with HIV-1 antiretroviral drugs (ARVs) and mutations in HIV reverse transcriptase (RT), protease, and integrase. There are five types of interactive query pages: Treatment Profiles (Protease and RT inhibitors) Mutation Profiles (Protease and RT mutations) Detailed Treatment Queries (Protease, RT, and integrase inhibitors) Detailed Mutation Queries (Protease, RT, and integrase mutations) Mutation Prevalence According to Subtype and Treatment Genotype-Phenotype Correlations The main page of the Genotype-Phenotype Correlations section links to four interactive query pages: three dynamically updated data summaries and one regularly updated downloadable dataset. Drug Resistance Positions Query for levels of resistance associated with known drug resistance mutations Detailed Phenotype Queries Queries for levels of resistance associated with individual mutations or mutation combinations at all positions of protease, RT, and integrase Patterns of Drug Resistance Mutations Downloadable Reference Dataset Genotype-Clinical Correlations This part of the database has two main sections: Clinical Trials Datasets Summaries of Clinical Studies References This part of the database has two main sections: one with summaries of the data from each of the references in HIVDB and one in which every primate immunodeficiency virus sequence in GenBank is annotated according to its presence or absence in HIVDB. Studies in HIVDB GenBank <=> HIVDB New Submissions Approximately every three months, the New Submissions section lists the studies that have been entered into HIVDB. The study title links to the introductory page of the study in the References section. Database Statistics (http://hivdb.stanford.edu/pages/HIVdbStatistics.html) 2. INTERACTIVE PROGRAMS HIVDB has seven main interactive programs. 1. HIVdb Program Mutation List Analysis Sequence Analysis HIVdb Output Sierra Web Service Release Notes Algorithm Specification Interface (ASI) 2. HIValg Program 3. HIVseq Program 4. Calibrated Population Resistance (CPR) tool 5. Mutation ARV Evidence Listing (MARVEL) 6. ART-AiDE 7. Rega HIV-1 Subtyping tool Three programs in the HIV Drug Resistance Database share a common code base: HIVseq, HIVdb, and HIValg. HIVseq accepts user-submitted protease, RT, and integrase sequences, compares them to the consensus subtype B reference sequence, and uses the differences as query parameters for interrogating the HIV Drug Resistance database (Shafer, D Jung, & B Betts, Nat Med 2000; Rhee SY et al. AIDS 2006). The query result provides users with the prevalence of protease, RT and integrase mutations according to subtype and PI, nucleoside RT inhibitor (NRTI), non-nucleoside RT inhibitor (NNRTI), and integrase inhibitor (INI) exposure. This allows users to detect unusual sequence results immediately so that the person doing the sequencing can check the primary sequence output while it is still on the desktop. In addition, unexpected associations between sequences or isolates can be discovered by immediately retrieving data on isolates sharing one or more mutations with the sequence. There are three ways in which the HIVdb program can be used: (i) entering a list of protease and RT mutations, (ii) entering a complete sequence containing protease, RT, and/or integrase, and (iii) using a Web Service. HIVdb is an expert system that accepts user-submitted HIV-1 pol sequences and returns inferred levels of resistance to 20 FDA-approved ARV drugs including 8 PIs, 7 NRTIs, 4 NNRTIs, and - with this update - one INI. In the HIVdb system, each HIV-1 drug resistance mutation is assigned a drug penalty score and a comment; the total score for a drug is derived by adding the scores of each mutation associated with resistance to that drug. Using the total drug score, the program reports one of the following levels of inferred drug resistance: susceptible, potential low-level resistance, low-level resistance, intermediate resistance, and high-level resistance. HIValg is designed for users interested in comparing the results of different algorithms or who are interested in comparing and evaluating existing and newly developed algorithms. The ability to develop new algorithms that can be run on the HIV Drug Resistance Database depends on the Algorithm Specific Interface (ASI) compiler (Shafer & Betts JCM 2003). Submission of Sequences and Mutations For each of the three programs, sequences can be entered using either the Sequence Analysis Form or the Mutation List form. 3. EDUCATIONAL RESOURCES HIVDB contains several regularly updated sections summarizing data linking RT, protease, and integrase mutations and antiretroviral drugs (ARVs). These sections include (i) tabular summaries of the major mutations associated with each ARV class, (ii) detailed summaries of the major, minor, and accessory mutations associated with each ARV, (iii) the comments used by the HIVdb program, (iv) the scores used by the HIVdb program, (v) clinical studies in which baseline drug resistance mutations have been correlated with the virological response (clinical outcome) to a specific ARV, (vi) mutations that can be used for drug resistance surveillance, and (vii) a two-page PDF handout. 1. Drug Resistance Summaries Tabular Drug Resistance Summaries by ARV Class Detailed Drug Resistance Summaries by ARV Drug Resistance Mutation Comments Used by the HIVdb Program Drug Resistance Mutation Scores Used by the HIVdb Program Genotype-Clinical Outcome Correlation Studies 2. Surveillance Drug-Resistance Mutation List Section 3. PDF Handout Grant Support 1. National Institute for Allergy and Infectious Diseases (NIAID, NIH): Online HIV Drug Resistance Database (PI: Robert W. Shafer, MD, 1R01AI68581-01A1), 04/01/06 - 3/31/11 2. National Institute for Allergy and Infectious Diseases (NIAID, NIH) supplement to the grant Identification of Multidrug-Resistant HIV-1 Isolates (PI: Robert W. Shafer, MD, AI46148-01): Supplement provided 1999-2005. 3. NIH/NIGMS Program Project on AIDS Structural Biology Program Project: Targeting Ensembles of Drug Resistant Protease Variants (PI: Celia Schiffer, PhD, University of Massachusetts): 2002-2007 4. University-wide AIDS Research Program (CR03-ST-524). Community collaborative award: Optimizing Clinical HIV Genotypic Resistance Interpretation: Principal Investigators: Robert W. Shafer, MD and W. Jeffrey Fessel MD (Kaiser Permanente Medical Care Program): 2004-2005 5. Stanford University Bio-X Interdisciplinary Initiative: HIV Gene Sequence Analysis for Drug Resistance Studies: A Pharmacogenetic Challenge Principal Investigators: Robert W. Shafer, MD and Daphne Koller, Ph.D. (Computer Science): 2000-2002

Proper citation: Stanford University HIV Drug Resistance Database (RRID:SCR_006631) Copy   

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https://swisstree.vital-it.ch/

Project that aims to provide a collection of Gold Standard gene phylogenies to the scientific community. This set of reference gene trees is suitable for phylogenomic databases to assess their current quality status, measure changes following new database releases and diagnose improvements subsequent to an upgrade of the analysis procedure.

Proper citation: SwissTree (RRID:SCR_015881) Copy   

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

Database that provides access to biological systems and their component genes, proteins, and small molecules, as well as literature describing those biosystems and other related data throughout Entrez. A biosystem, or biological system, is a group of molecules that interact directly or indirectly, where the grouping is relevant to the characterization of living matter. BioSystem records list and categorize components, such as the genes, proteins, and small molecules involved in a biological system. The companion FLink tool, in turn, allows you to input a list of proteins, genes, or small molecules and retrieve a ranked list of biosystems. A number of databases provide diagrams showing the components and products of biological pathways along with corresponding annotations and links to literature. This database was developed as a complementary project to (1) serve as a centralized repository of data; (2) connect the biosystem records with associated literature, molecular, and chemical data throughout the Entrez system; and (3) facilitate computation on biosystems data. The NCBI BioSystems Database currently contains records from several source databases: KEGG, BioCyc (including its Tier 1 EcoCyc and MetaCyc databases, and its Tier 2 databases), Reactome, the National Cancer Institute's Pathway Interaction Database, WikiPathways, and Gene Ontology (GO). It includes several types of records such as pathways, structural complexes, and functional sets, and is desiged to accomodate other record types, such as diseases, as data become available. Through these collaborations, the BioSystems database facilitates access to, and provides the ability to compute on, a wide range of biosystems data. If you are interested in depositing data into the BioSystems database, please contact them.

Proper citation: NCBI BioSystems Database (RRID:SCR_004690) Copy   

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http://clinicaltrials.gov/

Registry and results database of federally and privately supported clinical trials conducted in United States and around world. Provides information about purpose of trial, who may participate, locations, and phone numbers for more details. This information should be used in conjunction with advice from health care professionals.Offers information for locating federally and privately supported clinical trials for wide range of diseases and conditions. Research study in human volunteers to answer specific health questions. Interventional trials determine whether experimental treatments or new ways of using known therapies are safe and effective under controlled environments. Observational trials address health issues in large groups of people or populations in natural settings. ClinicalTrials.gov contains trials sponsored by National Institutes of Health, other federal agencies, and private industry. Studies listed in database are conducted in all 50 States and in 178 countries.

Proper citation: ClinicalTrials.gov (RRID:SCR_002309) Copy   

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http://www.who.int/ictrp/en/

Public database of information about all clinical trials involving humans, this global initiative provides a single point of access to information about ongoing and completed clinical trials. It contains the trial registration data sets made available by data providers around the world meeting criteria for content and quality control. It also aims to: * To improve the comprehensiveness, completeness and accuracy of registered clinical trial data * To communicate and raise awareness of the need to register clinical trials * To ensure the accessibility of registered data * To build capacity for clinical trial registration * To encourage the utilization of registered data * To ensure the sustainability of the ICTRP The mission of the WHO International Clinical Trials Registry Platform is to ensure that a complete view of research is accessible to all those involved in health care decision making. This will improve research transparency and will ultimately strengthen the validity and value of the scientific evidence base. The registration of all interventional trials is a scientific, ethical and moral responsibility. The ICTRP: * Publishes the ICTRP Search Portal * Supports the WHO Registry Network * Supports countries and regions wanting to establish WHO-compliant clinical trial registries or policies on trial registration.

Proper citation: WHO International Clinical Trials Registry Platform (RRID:SCR_004475) Copy   

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http://www.crossmodel.org/

An international consortium whose goals are to enable faster comparative studies and develop tools that make analysis accessible to the wider scientific community. InterMOD is an open source data warehouse where users can query and input their own data, access analysis tools, and create their own InterMine. Five core mines make make up InterMOD: RGD, SGD ZFIN, MGI, and WormBase.

Proper citation: InterMOD (RRID:SCR_013808) Copy   

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http://www.ebi.ac.uk/cgi-bin/sva/sva.pl/

THIS RESOURCE IS NO LONGER IN SERVICE.Documented on September 23,2022. The ENA Sequence Version Archive is a repository of all entries which have ever appeared in EMBL-Bank Sequence Database. You can browse the archive or use the batch retrieval form.

Proper citation: ENA Sequence Version Archive (RRID:SCR_000929) Copy   

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http://neuromorpho.org/index.jsp

Centrally curated inventory of digitally reconstructed neurons associated with peer-reviewed publications that contains some of the most complete axonal arborizations digitally available in the community. Each neuron is represented by a unique identifier, general information (metadata), the original and standardized ASCII files of the digital morphological reconstruction, and a set of morphometric features. It contains contributions from over 100 laboratories worldwide and is continuously updated as new morphological reconstructions are collected, published, and shared. Users may browse by species, brain region, cell type or lab name. Users can also download morphological reconstructions for research and analysis. Deposition and distribution of reconstruction files ultimately prevents data loss. Centralized curation and annotation aims at minimizing the effort required by data owners while ensuring a unified format. It also provides a one-stop entry point for all available reconstructions, thus maximizing data visibility and impact.

Proper citation: NeuroMorpho.Org (RRID:SCR_002145) Copy   

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http://www.fimre.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 7, 2022. Federation of International Mouse Resources (FIMRe) is a collaborating group of Mouse Repository and Resource Centers worldwide whose collective goal is to archive and provide strains of mice as cryopreserved embryos and gametes, ES cell lines, and live breeding stock to the research community. Goals of the Federation of International Mouse Resources: * Coordinate repositories and resource centers to: ** archive valuable genetically defined mice and ES cell lines being created worldwide ** meet research demand for these genetically defined mice and ES cell lines * Establish consistent, highest quality animal health standards in all resource centers * Provide genetic verification and quality control for genetic background and mutations * Provide resource training to enhance user ability to utilize cryopreserved resources

Proper citation: Federation of International Mouse Resources (RRID:SCR_006137) Copy   

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http://www.neuroinf.de

Portal used to coordinate activities of the German portion of the INCF group. The main focus is the development and free distribution of software tools for handling and analyzing neurophysiological data.

Proper citation: German Neuroinformatics Node (G-Node) (RRID:SCR_007279) Copy   

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http://www.microvesicles.org/

Web based database of proteins, RNA, lipids and metabolites that are identified in extracellular vesicles. Compendium for extracellular vesicles with continuous community annotation and with manually curated data from published literature.

Proper citation: Vesiclepedia (RRID:SCR_019011) Copy   

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http://www.biobanks.se/medicalbiobank.htm

A biobank created from a cross-sectional population of a town in Sweden. The Medical Biobank is mainly based on three cohorts: The V��sterbotten intervention cohort, the MONICA-cohort, and the Mammary screening cohort. These sub-cohorts together are named Northern Sweden Health and Disease Study Cohort (North Health). These sub-cohorts together is named Northern Sweden Health and Disease Study Cohort (North Health). Originally, the V��sterbotten Intervention program (VIP) is a long-term project intended for health promotion of the population of V��sterbotten. All individuals 40, 50 and 60 years of age in the population of the county are invited for screening (approx. 254.000 inhabitants). They are asked to complete a questionnaire concerning various lifestyle factors including diet. They are also asked to donate a separate blood sample to the Medical Biobank for freeze storage for later research purposes. The project started in 1985 and the cohort covered in December 2002, 74,000 individuals, of whom 67,000 had donated blood samples. The material is supplemented with population based samples from a local mammary screening (44,000 sampling occasions, 25,700 unique individuals) and from the Northern Sweden MONICA Project (11,500 sampling occasions, 7,500 unique individuals). The total cohort contains at the moment 85.000 unique individuals with 130.000 sampling occasions. The VIP and MONICA cohorts are population based and the mammary screening cohort are nearly population based. Follow-up: * For the VIP-cohort a second sample (and questionnaire) is collected with a 10-year interval of the individuals within the cohort. * Repeated sampling was performed in the MONICA project in 1999 on individuals participating in 1986, 1990, and 1994. * From 1997 repeated screening has started within the mammary screening program with sampling every second year, in the age group 50-69 years within the county. Biobank content: * Life-Style Questionnaire: Every attending subject is asked to answer a questionnaire, which in the VIP and MONICA-projects includes questions about education, occupation/working conditions, daily habits including smoking, diet, etc and in the mammary screening cohort on reproductive conditions. The dietary questionnaire has been validated twice. The data from the questionnaires, as well as from results from the biobank, are kept in a database for future research purposes. The questionnaires in the VIP and the MONICA project are optically read. * Measurements: Blood Pressure, Anthropometry, Glucose Tolerance Test, Blood Lipids * Blood Samples: The attendants are asked for their willingness to donate a sample of 20-ml whole blood for future analyses. The sample is taken after 4 hours of fasting or in the morning after an over night fasting (most samples) in the VIP and MONICA cohorts. The 20-ml sample is divided into 10 subsamples consisting of 6 plasma, 2 leukocyte (buffy coat) and 2 erythrocyte samples. All material is frozen at -80 degrees C. The organization of the bank is elaborated with specially trained staff and an organization of transport-, storage- and security facilities. For DNA handling a specialized laboratory has been built up. * End-points: Mortality, Cancer events, Cardiovascular events, Other morbidity, Other registry-based follow-up * Registries: At regular intervals the cohort is scanned for incident myocardial infarctions (MI) and stroke utilizing the Northern Sweden MONICA registry and for cancer using the regional cancer registry. In the future the same procedure will be applied also on other registries e.g. diabetes, osteoporosis, dementia.

Proper citation: Medical Biobank (RRID:SCR_010748) Copy   

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https://www.genome-cloud.com/user/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 29, 2019. A cloud platform for next-generation sequencing analysis and storage. Services include: * g-Analysis: Automated genome analysis pipelines at your fingertips * g-Cluster: Easy-of-use and cost-effective genome research infrastructure * g-Storage: A simple way to store, share and protect data * g-Insight: Accurate analysis and interpretation of biological meaning of genome data

Proper citation: GenomeCloud (RRID:SCR_011886) Copy   

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

NIH genetic sequence database that provides annotated collection of all publicly available DNA sequences for almost 280 000 formally described species (Jan 2014) .These sequences are obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects, including whole-genome shotgun (WGS) and environmental sampling projects. Most submissions are made using web-based BankIt or standalone Sequin programs, and GenBank staff assigns accession numbers upon data receipt. It is part of International Nucleotide Sequence Database Collaboration and daily data exchange with European Nucleotide Archive (ENA) and DNA Data Bank of Japan (DDBJ) ensures worldwide coverage. GenBank is accessible through NCBI Entrez retrieval system, which integrates data from major DNA and protein sequence databases along with taxonomy, genome, mapping, protein structure and domain information, and biomedical journal literature via PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of GenBank database are available by FTP.

Proper citation: GenBank (RRID:SCR_002760) Copy   

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http://www.enzyme-database.org

Enzyme database developed as a way to access the data of the IUBMB Enzyme Nomenclature List. The data, which are stored in a MySQL database, preserve the formatting of chemical names according to IUPAC standards. A simple, easy to use, web-based query interface is provided (Search), along with an advanced search engine for more complex queries (Advanced Search). Forms are provided to submit suggestions for new enzyme entries or to report errors in existing entries. Downloads of the database are available via FTP as SQL or XML.

Proper citation: ExplorEnz (RRID:SCR_002665) Copy   

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http://idm.fudan.edu.cn/PBmice/

Database for storing, retrieving, and displaying the information derived from piggyBac (PB) insertions (Insert) and their characterizations in the mouse genome with piggyBac transposon system. Quick Search and Advanced Search tools have been provided to find information in the PBmice database, the result is centered on Inserts and provides information related to the Inserts. A mapping database is linked to PBmice too. This mapping database allows row experiment data to be inputted in. All the mature data can be allowed publish to PBmice. PBmice Source Code is available with a License Agreement.

Proper citation: PBmice (RRID:SCR_006978) Copy   

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http://opensnp.org/

Database of raw data from people who have shared their direct-to-customer (DTC) genetic results from 23andMe, deCODEme or FamilyTreeDNA. Logged-In users can search the database for users with specific phenotypes and mass-download all corresponding SNP-datasets. This allows you to get datasets like All genotyping files of openSNP-users that have Alzheimer and the corresponding control group. They are currently working on providing API-access. You can also use JSON to get access to openSNP-data and some other ways: If you want to automate the file-downloads for a given phenotype the RSS-feeds could help you. Inside the RSS-XML there are 2 flags you could use to automatically create correct genotype-groups: gives you the variation of this user at the phenotype you are looking at and gives you the download link. If you were genotyped by 23andMe, deCODEme or FamilyTreeDNA (contact them regarding others) you can upload the raw genotype data which you can download from your DTC test provider. The data will then be openly available for the world to see and download. They also parse these SNPs and annotate them. For annotation they include the manually curated SNPedia and find Open Access primary publications which appear in the journals of The Public Library of Science (PLoS), an Open Access publishing group. Additionally they screen Mendeley, a crowd-sourced repository of scientific publications. You can also publish some of your phenotypes so some day it might get possible to associate some SNPs with phenotypes. You can also share your knowledge about SNPs and phenotypes with other users and can socialize.

Proper citation: openSNP (RRID:SCR_001636) Copy   

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