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http://www.researchgate.net/

A professional, social network and publication database geared to researchers where the latest field specific publications can be read, publications with other specialists can be discussed, and collaboration with colleagues is facilitated. They provide researchers with access to around 40 million abstracts and tens of thousands of Full texts, uploaded by the authors themselves. Researchers can search through 7 of the largest databases simultaneously, such as PubMed, IEEE & CiteSeer.

Proper citation: ResearchGate (RRID:SCR_006505) Copy   

•   Source: SciCrunch Registry

http://www.phytozome.net/

A comparative platform for green plant genomics. Families of orthologous and paralogous genes that represent the modern descendents of ancestral gene sets are constructed at key phylogenetic nodes. These families allow easy access to clade specific orthology / paralogy relationships as well as clade specific genes and gene expansions. As of release v9.1, Phytozome provides access to forty-one sequenced and annotated green plant genomes which have been clustered into gene families at 20 evolutionarily significant nodes. Where possible, each gene has been annotated with PFAM, KOG, KEGG, and PANTHER assignments, and publicly available annotations from RefSeq, UniProt, TAIR, JGI are hyper-linked and searchable., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Phytozome (RRID:SCR_006507) Copy   

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https://repository.niddk.nih.gov/home/

NIDDK Central Repositories are two separate contract funded components that work together to store data and samples from significant, NIDDK funded studies. First component is Biorepository that gathers, stores, and distributes biological samples from studies. Biorepository works with investigators in new and ongoing studies as realtime storage facility for archival samples.Second component is Data Repository that gathers, stores and distributes incremental or finished datasets from NIDDK funded studies Data Repository helps active data coordinating centers prepare databases and incremental datasets for archiving and for carrying out restricted queries of stored databases. Data Repository serves as Data Coordinating Center and website manager for NIDDK Central Repositories website.

Proper citation: NIDDK Central Repository (RRID:SCR_006542) Copy   

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http://www.informatics.jax.org/expression.shtml

Community database that collects and integrates the gene expression information in MGI with a primary emphasis on endogenous gene expression during mouse development. The data in GXD are obtained from the literature, from individual laboratories, and from large-scale data providers. All data are annotated and reviewed by GXD curators. GXD stores and integrates different types of expression data (RNA in situ hybridization; Immunohistochemistry; in situ reporter (knock in); RT-PCR; Northern and Western blots; and RNase and Nuclease s1 protection assays) and makes these data freely available in formats appropriate for comprehensive analysis. There is particular emphasis on endogenous gene expression during mouse development. GXD also maintains an index of the literature examining gene expression in the embryonic mouse. It is comprehensive and up-to-date, containing all pertinent journal articles from 1993 to the present and articles from major developmental journals from 1990 to the present. GXD stores primary data from different types of expression assays and by integrating these data, as data accumulate, GXD provides increasingly complete information about the expression profiles of transcripts and proteins in different mouse strains and mutants. GXD describes expression patterns using an extensive, hierarchically-structured dictionary of anatomical terms. In this way, expression results from assays with differing spatial resolution are recorded in a standardized and integrated manner and expression patterns can be queried at different levels of detail. The records are complemented with digitized images of the original expression data. The Anatomical Dictionary for Mouse Development has been developed by our Edinburgh colleagues, as part of the joint Mouse Gene Expression Information Resource project. GXD places the gene expression data in the larger biological context by establishing and maintaining interconnections with many other resources. Integration with MGD enables a combined analysis of genotype, sequence, expression, and phenotype data. Links to PubMed, Online Mendelian Inheritance in Man (OMIM), sequence databases, and databases from other species further enhance the utility of GXD. GXD accepts both published and unpublished data.

Proper citation: Gene Expression Database (RRID:SCR_006539) Copy   

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http://www.rarechromo.org/html/home.asp

Unique is a source of information and support to families and individuals affected by any rare chromosome disorder and to the professionals who work with them. Unique is a UK-based charity but welcomes members worldwide. Unique''''s Karyotype Database allows users to search the Registered Chromosome Disorders by chromosome, arm and disorder. You may have been given a diagnosis or indication of a chromosome disorder by a geneticist or other medical professional and they may have used a medical term which is unfamiliar to you. So to help you decide if Unique is the appropriate organization for you, we thought it would be useful to describe the different categories of rare chromosome disorder. Rare chromosome disorders can be grouped as structural disorders, numerical disorders and other miscellaneous disorders. Unique: * acts as an international family support group * produces a newsletter three times each year * works to promote awareness of rare chromosome disorders * arranges for families to assist in research into rare chromosome disorders * links families whose children have similar clinical and/or practical problems * works to ensure that the public at large are aware of rare chromosome disorders * works to raise funds to support the group activities and produce literature to make others more aware of our children''''s conditions * assists relevant research projects and the centralisation of information, at all times observing the need for total confidentiality * sets up local groups throughout the UK for families affected by any rare chromosome disorders and to give support and encouragement to each other * develops and maintains a comprehensive computerised database detailing the life-time effects of specific chromosome disorders on affected members * aims to hold an annual conference where families and relevant specialists can meet and be informed of the latest medical, technical and practical developments * liaises and works in co-operation, with other similar support groups and professionals world-wide for the benefit of families and individuals affected by rare chromosome disorders * ensures that hospitals, doctors, health authorities, genetic clinics and other professionals are aware of the group so that we may have early contact with families where required Membership of Unique is free but the group receives no government funding and is heavily reliant on donations and fundraising to continue its work. Please help us in whatever way you can.

Proper citation: Unique (RRID:SCR_006492) Copy   

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http://www.LOVD.nl/

Freely available tool for Gene-centered collection and display of DNA variations. It also provides patient-centered data storage and storage of Next Generation Sequencing (NGS) data, even of variants outside of genes. Please note that LOVD provides a system for storage of information on genes and allelic variants. To obtain information about any genes or variants, do not download the LOVD package. This information should be obtained from the respective databases, http://www.lovd.nl/2.0/index_list.php In total: 2,507,027 variants (2,208,937 unique) in 170,935 individuals in 62619 genes in 88 LOVD installations. (Aug. 2013) LOVD 3.0 shared installation, http://databases.lovd.nl/shared/genes To maintain a high quality of the data stored, LOVD connects with various resources, like HGNC, NCBI, EBI and Mutalyzer. You can download LOVD in ZIP and GZIPped TARball formats.

Proper citation: Leiden Open Variation Database (RRID:SCR_006566) Copy   

•   Source: SciCrunch Registry

http://omim.org

Online catalog of human genes and genetic disorders, for clinical features, phenotypes and genes. Collection of human genes and genetic phenotypes, focusing on relationship between phenotype and genotype. Referenced overviews in OMIM contain information on all known mendelian disorders and variety of related genes. It is updated daily, and entries contain copious links to other genetics resources.

Proper citation: OMIM (RRID:SCR_006437) Copy   

•   Source: SciCrunch Registry

http://gmd.mpimp-golm.mpg.de/

It facilitates the search for and dissemination of mass spectra from biologically active metabolites quantified using Gas chromatography (GC) coupled to mass spectrometry (MS). Use the Search Page to search for a compound of your interest, using the name, mass, formula, InChI etc. as query input. Additionally, a Library Search service enables the search of user submitted mass spectra within the GMD. In parallel to the library search, a prediction of chemical sub-groups is performed. This approach has reached beta level and a publication is currently under review. Using several sub-group specific Decision Trees (DTs), mass spectra are classified with respect to the presence of the chemical moieties within the linked (unknown) compound. Prediction of functional groups (ms analysis) facilitates the search of metabolites within the GMD by means of user submitted GC-MS spectra consisting of retention index (n-alkanes, if vailable) and mass intensities ratios. In addition, a functional group prediction will help to characterize those metabolites without available reference mass spectra included in the GMD so far. Instead, the unknown metabolite is characterized by predicted presence or absence of functional groups. For power users this functionality presented here is exposed as soap based web services. Functional group prediction of compounds by means of GC-EI-MS spectra using Microsoft analysis service decision trees All currently available trained decision trees and sub-structure predictions provided by the GMD interface. Table describes the functional group, optional use of an RI system, record date of the trained decision tree, number of MSTs with proportion of MSTs linked to metabolites with the functional group present for each tree. Average and standard deviation of the 50-fold CV error, namely the ratio false over correctly sorted MSTs in the trained DT, are listed. The GMD website offers a range of mass spectral reference libraries to academic users which can be downloaded free of charge in various electronic formats. The libraries are constituted by base peak normalized consensus spectra of single analytes and contain masses in the range 70 to 600 amu, while the ubiquitous mass fragments typically generated from compounds carrying a trimethylsilyl-moiety, namely the fragments at m/z 73, 74, 75, 147, 148, and 149, were excluded.

Proper citation: GMD (RRID:SCR_006625) Copy   

•   Source: SciCrunch Registry

http://www.thegpm.org/

The Global Proteome Machine Organization was set up so that scientists involved in proteomics using tandem mass spectrometry could use that data to analyze proteomes. The projects supported by the GPMO have been selected to improve the quality of analysis, make the results portable and to provide a common platform for testing and validating proteomics results. The Global Proteome Machine Database was constructed to utilize the information obtained by GPM servers to aid in the difficult process of validating peptide MS/MS spectra as well as protein coverage patterns. This database has been integrated into GPM server pages, allowing users to quickly compare their experimental results with the best results that have been previously observed by other scientists.

Proper citation: Global Proteome Machine Database (GPM DB) (RRID:SCR_006617) Copy   

•   Source: SciCrunch Registry

http://www.usrds.org/

Annual report, standard analysis files and an online query system from the national data registry on the end-stage renal disease (ESRD) population in the U.S., including treatments and outcomes. The Annual Data Report is divided into two parts. The Atlas section displays data using graphs and charts. Specific chapters address trends in ESRD patient populations, quality of ESRD care, kidney transplantation outcomes, costs of ESRD care, Healthy People 2010 objectives, chronic kidney disease, pediatric ESRD, and cardiovascular disease special studies. The Reference Tables are devoted entirely to the ESRD population. The RenDER (Renal Data Extraction and Referencing) online data query system allows users to build data tables and maps for the ESRD population. National, state, and county level data are available. USRDS staff collaborates with members of Centers for Medicare & Medicaid Services (CMS), the United Network for Organ Sharing (UNOS), and the ESRD networks, sharing datasets and actively working to improve the accuracy of ESRD patient information.

Proper citation: United States Renal Data System (RRID:SCR_006699) Copy   

•   Source: SciCrunch Registry

https://www.iedb.org/

Repository contains antibody/B cell and T cell epitope information and epitope prediction and analysis tools. Immune epitopes are defined as molecular structures recognized by specific antigen receptors of the immune system, namely antibodies, B cell receptors, and T cell receptors. Immune epitopes from infectious diseases, excluding HIV, and immune-mediated diseases and the accompanying biological information are included.

Proper citation: Immune Epitope Database and Analysis Resource (IEDB) (RRID:SCR_006604) Copy   

•   Source: SciCrunch Registry

http://rdp.cme.msu.edu

A database which provides ribosome related data services to the scientific community, including online data analysis, rRNA derived phylogenetic trees, and aligned and annotated rRNA sequences. It specifically contains information on quality-controlled, aligned and annotated bacterial and archaean 16S rRNA sequences, fungal 28S rRNA sequences, and a suite of analysis tools for the scientific community. Most of the RDP tools are now available as open source packages for users to incorporate in their local workflow.

Proper citation: Ribosomal Database Project (RRID:SCR_006633) Copy   

•   Source: SciCrunch Registry

http://rice.plantbiology.msu.edu/

Database and resource that provides sequence and annotation data for the rice genome. This website provides genome sequence from the Nipponbare subspecies of rice and annotation of the 12 rice chromosomes. All structural and functional annotation is viewable through our Rice Genome Browser which currently supports 75 tracks of annotation. Enhanced data access is available through web interfaces, FTP downloads and a Data Extractor tool developed in order to support discrete dataset downloads. Rice is a model species for the monocotyledonous plants and the cereals which are the greatest source of food for the world''s population. While rice genome sequence is available through multiple sequencing projects, high quality, uniform annotation is required in order for genome sequence data to be fully utilized by researchers. The existence of a common gene set and uniform annotation allows researchers within the rice community to work from a common resource so that their results can be more easily interpreted by other scientists. The objective of this project has always been to provide high quality annotation for the rice genome. They generated, refined and updated gene models for the estimated 40,000-60,000 total rice genes, provided standardized annotation for each model, linked each model to functional annotation including expression data, gene ontologies, and tagged lines. They have provided a resource to extend the annotation of the rice genome to other plant species by providing comparative alignments to other plant species. Analysis/Tools are available including: BLAST, Locus Name Search, Functional Term Search, Protein Domain Search, Anatomy Expression Viewer, Highly Expressed Genes

Proper citation: Rice Genome Annotation (RRID:SCR_006663) Copy   

•   Source: SciCrunch Registry

http://www.innatedb.com

Publicly available database of the genes, proteins, experimentally-verified interactions and signaling pathways involved in the innate immune response of humans, mice and bovines to microbial infection. The database captures coverage of the innate immunity interactome by integrating known interactions and pathways from major public databases together with manually-curated data into a centralized resource. The database can be mined as a knowledgebase or used with the integrated bioinformatics and visualization tools for the systems level analysis of the innate immune response. Although InnateDB curation focuses on innate immunity-relevant interactions and pathways, it also incorporates detailed annotation on the entire human, mouse and bovine interactomes by integrating data (178,000+ interactions & 3,900+ pathways) from several of the major public interaction and pathway databases. InnateDB also has integrated human, mouse and bovine orthology predictions generated using Ortholgue software. Ortholgue uses a phylogenetic distance-based method to identify possible paralogs in high-throughput orthology predictions. Integrated human and mouse conserved gene order and synteny information has also been determined to provide further support for orthology predictions. InnateDB Capabilities: * View statistics for manually-curated innate immunity relevant molecular interactions. New manually curated interactions are submitted weekly. * Search for genes and proteins of interest. * Search for experimentally-verified molecular interactions by gene/protein name, interaction type, cell type, etc. * Search genes/interactions belonging to 3,900 pathways. * Visualize interactions using an intuitive subcellular localization-based layout in Cerebral. * Upload your own list of genes along with associated gene expression data (from up to 10 experimental conditions) to interactively analyze this data in a molecular interaction network context. Once you have uploaded your data, you will be able to interactively visualize interaction networks with expression data overlaid; carry out Pathway, Gene Ontology and Transcription Factor Binding Site over-representation analyses; construct orthologous interaction networks in other species; and much more. * Access curated interaction data via a dedicated PSICQUIC webservice.

Proper citation: InnateDB (RRID:SCR_006714) Copy   

•   Source: SciCrunch Registry

http://www.ars-grin.gov/

Web server to provide germplasm information about plants, animals, microbes, invertebrates and access to databases that maintain passport, characterization, evaluation, inventory, and distribution data for the management and utilization of national germplasm collections. Under control of the U.S. Department of Agriculture's Agricultural Research Service to support the National Genetic Resources Program (NGRP). Operated by the Database Management Unit of the National Germplasm Resource Laboratory in Beltsville, Maryland.

Proper citation: Germplasm Resources Information Network (RRID:SCR_006675) Copy   

•   Source: SciCrunch Registry

http://inparanoid.sbc.su.se/cgi-bin/index.cgi

Collection of pairwise comparisons between 100 whole genomes generated by a fully automatic method for finding orthologs and in-paralogs between TWO species. Ortholog clusters in the InParanoid are seeded with a two-way best pairwise match, after which an algorithm for adding in-paralogs is applied. The method bypasses multiple alignments and phylogenetic trees, which can be slow and error-prone steps in classical ortholog detection. Still, it robustly detects complex orthologous relationships and assigns confidence values for in-paralogs. The original data sets can be downloaded.

Proper citation: InParanoid: Eukaryotic Ortholog Groups (RRID:SCR_006801) Copy   

•   Source: SciCrunch Registry

http://www.peptideatlas.org

Multi-organism, publicly accessible compendium of peptides identified in a large set of tandem mass spectrometry proteomics experiments. Mass spectrometer output files are collected for human, mouse, yeast, and several other organisms, and searched using the latest search engines and protein sequences. All results of sequence and spectral library searching are subsequently processed through the Trans Proteomic Pipeline to derive a probability of correct identification for all results in a uniform manner to insure a high quality database, along with false discovery rates at the whole atlas level. The raw data, search results, and full builds can be downloaded for other uses. All results of sequence searching are processed through PeptideProphet to derive a probability of correct identification for all results in a uniform manner ensuring a high quality database. All peptides are mapped to Ensembl and can be viewed as custom tracks on the Ensembl genome browser. The long term goal of the project is full annotation of eukaryotic genomes through a thorough validation of expressed proteins. The PeptideAtlas provides a method and a framework to accommodate proteome information coming from high-throughput proteomics technologies. The online database administers experimental data in the public domain. You are encouraged to contribute to the database.

Proper citation: PeptideAtlas (RRID:SCR_006783) Copy   

•   Source: SciCrunch Registry

http://www.ensemblgenomes.org/

Database portal offering integrated access to genome-scale data from non-vertebrate species of scientific interest, developed using the Ensembl genome annotation and visualization platform. Ensembl Genomes consists of five sub-portals (for bacteria, protists, fungi, plants and invertebrate metazoa) designed to complement the availability of vertebrate genomes in Ensembl. Many of the databases supporting the portal have been built in close collaboration with the scientific community - essential for maintaining the accuracy and usefulness of the resource. A common set of user interfaces (which include a graphical genome browser, FTP, BLAST search, a query optimized data warehouse, programmatic access, and a Perl API) is provided for all domains. Data types incorporated include annotation of (protein and non-protein coding) genes, cross references to external resources, and high throughput experimental data (e.g. data from large scale studies of gene expression and polymorphism visualized in their genomic context). Additionally, extensive comparative analysis has been performed, both within defined clades and across the wider taxonomy, and sequence alignments and gene trees resulting from this can be accessed through the site.

Proper citation: Ensembl Genomes (RRID:SCR_006773) Copy   

•   Source: SciCrunch Registry

https://cansar.icr.ac.uk/

canSAR is an integrated database that brings together biological, chemical, pharmacological (and eventually clinical) data. Its goal is to integrate this data and make it accessible to cancer research scientists from multiple disciplines, in order to help with hypothesis generation in cancer research and support translational research. This cancer research and drug discovery resource was developed to utilize the growing publicly available biological annotation, chemical screening, RNA interference screening, expression, amplification and 3D structural data. Scientists can, in a single place, rapidly identify biological annotation of a target, its structural characterization, expression levels and protein interaction data, as well as suitable cell lines for experiments, potential tool compounds and similarity to known drug targets. canSAR has, from the outset, been completely use-case driven which has dramatically influenced the design of the back-end and the functionality provided through the interfaces. The Web interface provides flexible, multipoint entry into canSAR. This allows easy access to the multidisciplinary data within, including target and compound synopses, bioactivity views and expert tools for chemogenomic, expression and protein interaction network data.

Proper citation: canSAR (RRID:SCR_006794) Copy   

•   Source: SciCrunch Registry

http://prodom.prabi.fr/

Comprehensive set of protein domain families automatically generated from UniProt Knowledge Database. Automated clustering of homologous domains generated from global comparison of all available protein sequences., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: ProDom (RRID:SCR_006969) Copy   

•   Source: SciCrunch Registry