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http://geneticassociationdb.nih.gov/

The Genetic Association Database is an archive of human genetic association studies of complex diseases and disorders. The goal of this database is to allow the user to rapidly identify medically relevant polymorphism from the large volume of polymorphism and mutational data, in the context of standardized nomenclature. The data is from published scientific papers. Study data is recorded in the context of official human gene nomenclature with additional molecular reference numbers and links. It is gene centered. That is, each record is a record of a gene or marker. If a study investigated 6 genes for a particular disorder, there will be 6 records. Anyone may view this database and anyone may submit records. You do not have to be an author on the original study to submit a record. All submitted records will be reviewed before inclusion in the archive. Both genetic and environmental factors contribute to human diseases. Most common diseases are influenced by a large number of genetic and environmental factors, most of which individually have only a modest effect on the disease. Though genetic contributions are relatively well characterized for some monogenetic diseases, there has been no effort at curating the extensive list of environmental etiological factors. From a comprehensive search of the MeSH annotation of MEDLINE articles, they identified 3,342 environmental etiological factors associated with 3,159 diseases. They also identified 1,100 genes associated with 1,034 complex diseases from the NIH Genetic Association Database (GAD), a database of genetic association studies. 863 diseases have both genetic and environmental etiological factors available. Integrating genetic and environmental factors results in the etiome, which they define as the comprehensive compendium of disease etiology.

Proper citation: Genetic Association Database (RRID:SCR_013264) Copy   

•   Source: SciCrunch Registry

http://marinespecies.org/

An authoritative and comprehensive list of names of marine organisms, including information on synonymy. While highest priority goes to valid names, other names in use are included so that this register can serve as a guide to interpret taxonomic literature. The content of WoRMS is controlled by taxonomic experts, not by database managers. WoRMS has an editorial management system where each taxonomic group is represented by an expert who has the authority over the content, and is responsible for controlling the quality of the information. Each of these main taxonomic editors can invite several specialists of smaller groups within their area of responsibility to join them. This register of marine species grew out of the European Register of Marine Species (ERMS), and its combination with several other species registers maintained at the Flanders Marine Institute (VLIZ). Rather than building separate registers for all projects, and to make sure taxonomy used in these different projects is consistent, VLIZ developed a consolidated database called ''Aphia''. A list of marine species registers included in Aphia is available below. MarineSpecies.org is the web interface for this database. The WoRMS is an idea that is being developed, and will combine information from Aphia with other authoritative marine species lists which are maintained by others (e.g. AlgaeBase, FishBase, Hexacorallia, NeMys). Resources to build MarineSpecies.org and Aphia were provided mainly by the EU Network of Excellence ''Marine Biodiversity and Ecosystem Functioning'' (MarBEF), and also by the EU funded Species 2000 Europe and ERMS projects. Intellectual property rights of the European part of the register is managed through the Society for the Management of Electronic Biodiversity Data (SMEBD). Similar solutions are now being investigated for the other parts of the register.

Proper citation: WoRMS (RRID:SCR_013312) Copy   

•   Source: SciCrunch Registry

http://www.epa.gov/iris/

IRIS is a toxicology data file on the National Library of Medicine''s (NLM) Toxicology Data Network. It contains data in support of human health risk assessment. It is compiled by the U.S. Environmental Protection Agency (EPA) and contains over 500 chemical records. It is a compilation of electronic reports on specific substances found in the environment and their potential to cause human health effects. IRIS was initially developed for EPA staff in response to a growing demand for consistent information on substances for use in risk assessments, decision-making and regulatory activities. The information in IRIS is intended for those without extensive training in toxicology, but with some knowledge of health sciences. The Integrated Risk Information System (IRIS) is an electronic database containing information on human health effects that may result from exposure to various substances in the environment. IRIS is prepared and maintained by the EPAs National Center for Environmental Assessment (NCEA) within the Office of Research and Development (ORD). The heart of the IRIS system is its collection of searchable documents that describe the health effects of individual substances and that contain descriptive and quantitative information in the following categories: -Noncancer effects: Oral reference doses and inhalation reference concentrations (RfDs and RfCs, respectively) for effects known or assumed to be produced through a nonlinear (possibly threshold) mode of action. In most instances, RfDs and RfCs are developed for the noncarcinogenic effects of substances. -Cancer effects: Descriptors that characterize the weight of evidence for human carcinogenicity, oral slope factors, and oral and inhalation unit risks for carcinogenic effects. Where a nonlinear mode of action is established, RfD and RfC values may be used.

Proper citation: Integrated Risk Information System (RRID:SCR_013005) Copy   

•   Source: SciCrunch Registry

http://pubmlst.org/

Database for molecular typing and microbial genome diversity.

Proper citation: PubMLST (RRID:SCR_012955) Copy   

•   Source: SciCrunch Registry

http://giardiadb.org

GiardiaDB is a resource for information on Giardia lamblia. It contains gene information, including genomic attributes, protein expression patterns, evolution, and EST sequence information. The website provides tools for BLASTing, sequence retrieval, graphic visualization, and PubMed information.

Proper citation: GiardiaDB (RRID:SCR_013377) Copy   

•   Source: SciCrunch Registry

http://www.syfpeithi.de/

SYFPEITHI is a database comprising more than 7000 peptide sequences known to bind class I and class II MHC molecules. The entries are compiled from published reports only. It contains a collection of MHC class I and class II ligands and peptide motifs of humans and other species, such as apes, cattle, chicken, and mouse, for example, and is continuously updated. Searches for MHC alleles, MHC motifs, natural ligands, T-cell epitopes, source proteins/organisms and references are possible. Hyperlinks to the EMBL and PubMed databases are included. In addition, ligand predictions are available for a number of MHC allelic products. The database is based on previous publications on T-cell epitopes and MHC ligands. It contains information on: -Peptide sequences -anchor positions -MHC specificity -source proteins, source organisms -publication references Since the number of motifs continuously increases, it was necessary to set up a database which facilitates the search for peptides and allows the prediction of T-cell epitopes. The prediction is based on published motifs (pool sequencing, natural ligands) and takes into consideration the amino acids in the anchor and auxiliary anchor positions, as well as other frequent amino acids. The score is calculated according to the following rules: The amino acids of a certain peptide are given a specific value depending on whether they are anchor, auxiliary anchor or preferred residue. Ideal anchors will be given 10 points, unusual anchors 6-8 points, auxiliary anchors 4-6 and preferred residues 1-4 points. Amino acids that are regarded as having a negative effect on the binding ability are given values between -1 and -3. Sponsors: SYFPEITHI is supported by DFG-Sonderforschungsbereich 685 and theEuropean Union: EU BIOMED CT95-1627, BIOTECH CT95-0263, and EU QLQ-CT-1999-00713.

Proper citation: SYFPEITHI: A Database for MHC Ligands and Peptide Motifs (RRID:SCR_013182) Copy   

•   Source: SciCrunch Registry

http://www.phosphonet.ca/

PhosphoNET is an open-access, online knowledgebase developed by Kinexus Bioinformatics Corporation to foster the study of cell signaling systems to advance biomedical research in academia and industry. PhosphoNET is the world''s largest repository of known and predicted information on human phosphorylation sites, their evolutionary conservation and the identities of protein kinases that may target these sites. Search by protein name, UniProt number, IPI number, or 15 AA P-site sequence. PhosphoNET presently holds data on over 650,000 known and putative phosphorylation sites (P-sites) in over 23,000 human proteins that have been collected from the scientific literature and other reputable websites. Over 14% of these phospho-sites have been experimentally validated. The rest have been predicted with a novel P-Site Predictor algorithm developed at Kinexus with academic partners at the University of British Columbia and Simon Fraser University. With the PhosphoNET Evolution module, this website also provides information about cognate proteins in over 20 other species that may share these human phospho-sites. This helps to define the most functionally important phospho-sites as these are expected to be highly conserved in nature. With the Kinase Predictor module, listings are provided for the top 50 human protein kinases that are likely to phosphorylate each of these phospho-sites using another proprietary kinase substrate prediction algorithm developed at Kinexus. Our kinase substrate predictions are based on deduced consensus phosphorylation site amino acid frequency scoring matrices that we have determined for each of ~500 different human protein kinases. The specificity matrices are generated directly from the primary amino acid sequences of the catalytic domains of these kinases, and when available, have proven to correlate strongly with substrate prediction matrices based on alignment of known substrates of these kinases. The higher the score, the better the prospect that a kinase will phosphorylate a given site. Over 30 million kinase-substrate phospho-site pairs are quantified in PhosphoNET. Kinexus Bioinformatics Corporation has the capability to test most of these putative interactions in vitro for our clients.

Proper citation: PhosphoNET (RRID:SCR_013070) Copy   

•   Source: SciCrunch Registry

http://www.hgsc.bcm.tmc.edu/

Center for high-throughput DNA sequence generation and the accompanying analysis. The sequence data generated by the center's machines are analyzed in a complex bioinformatics pipeline, and the data are deposited regularly in the public databases at the National Center for Biotechnology Information (NCBI).

Proper citation: Baylor College of Medicine Human Genome Sequencing Center (RRID:SCR_013605) Copy   

•   Source: SciCrunch Registry

http://www.dna.affrc.go.jp/PLACE/

A database of motifs found in plant cis-acting regulatory DNA elements, all from previously published reports. It covers vascular plants only. In addition to the motifs originally reported, their variations in other genes or in other plant species reported later are also compiled. The PLACE database also contains a brief description of each motif and relevant literature with PubMed ID numbers. DDBJ/EMBL/GenBank nucleotide sequence databases accession numbers will be also included. Note: As of January 2007, PLACE is no longer updated or maintained.

Proper citation: PLACE- A Database of Plant Cis-acting Regulatory DNA Elements (RRID:SCR_013428) Copy   

•   Source: SciCrunch Registry

http://data.kew.org/cvalues/

The DNA amount in the unreplicated gametic nucleus of an organism is referred to as its C-value, irrespective of the ploidy level of the taxon. The Plant DNA C-values Database currently contains data for 7058 plant species. It combines data from the Angiosperm DNA C-values Database, Gymnosperm DNA C-values Database, the Pteridophyte DNA C-values Database, the Bryophyte DNA C-values Database, together with the addition of the Algae DNA C-values database.

Proper citation: Plant DNA C-values Database (RRID:SCR_013434) Copy   

•   Source: SciCrunch Registry

http://web.stanford.edu/group/barres_lab/brain_rnaseq.html

Database containing RNA-Seq transcriptome and splicing data from glia, neurons, and vascular cells of cerebral cortex. Collection of RNA-Seq transcriptome and splicing data from glia, neurons, and vascular cells of mouse cerebral cortex. RNA-Seq of cell types isolated from mouse and human brain.

Proper citation: Brain RNA-Seq (RRID:SCR_013736) Copy   

•   Source: SciCrunch Registry

http://www.cyverse.org/

A google drive interface for scientific big data. CyVerse cyberinfrastructure is applicable to all life sciences disciplines and works equally well on data from plants, animals, or microbes. It provides life scientists with computational infrastructure to handle large datasets and complex analyses. Its extensible platforms provide data storage, bioinformatics tools, image analyses, cloud services, and APIs.

Proper citation: CyVerse (RRID:SCR_014531) Copy   

•   Source: SciCrunch Registry

https://tcia.at/

A database which provides results of comprehensive immunogenomic analyses of next generation sequencing data for 19 solid cancers from The Cancer Genome Atlas and other datasources. The database can be queried for the gene expression of specific immune-related gene sets, cellular composition of immune infiltrates (characterized using gene set enrichment analyses and deconvolution), neoantigens and cancer-germline antigens, HLA types, and tumor heterogeneity (estimated from cancer cell fractions). It also provides survival analyses for different types immunological parameters.

Proper citation: The Cancer Immunome Database (RRID:SCR_014508) Copy   

•   Source: SciCrunch Registry

https://xcmsonline.scripps.edu

Cloud-based mass spectrometry data processing platform for metabolomics and lipidomics.

Proper citation: XCMS (RRID:SCR_015538) Copy   

•   Source: SciCrunch Registry

http://gnomad.broadinstitute.org/

Database that aggregates exome and genome sequencing data from large-scale sequencing projects. The gnomAD data set contains individuals sequenced using multiple exome capture methods and sequencing chemistries. Raw data from the projects have been reprocessed through the same pipeline, and jointly variant-called to increase consistency across projects.

Proper citation: Genome Aggregation Database (RRID:SCR_014964) Copy   

•   Source: SciCrunch Registry

https://github.com/stamatak/ExaML

Source code for large-scale phylogenetic analyses on whole-transcriptome and whole-genome alignments using supercomputers.

Proper citation: Examl (RRID:SCR_016087) Copy   

•   Source: SciCrunch Registry

https://www.mzcloud.org

A mass spectral database that assists in identifying compunds in life sciences, matabolomics, pharmaceutical research, toxicology, forensic investigations, environemnta analysis, food control, and industry.

Proper citation: mzCloud (RRID:SCR_014669) Copy   

•   Source: SciCrunch Registry

http://predictsite.com

Patient database that contains EEG data sets, executable tasks, and computational tools., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PREDiCT (RRID:SCR_015517) Copy   

•   Source: SciCrunch Registry

http://www.apa.org/pubs/databases/psycinfo/

Database for published, indexed resources pertaining to psychological, psychiatric and other behavioral and social science research. Users can search for resources by document type, research methodology, and funding source.

Proper citation: PsycINFO (RRID:SCR_014799) Copy   

•   Source: SciCrunch Registry

http://www.massbank.jp/?lang=en

Public repository of mass spectral data which allows users to search similar spectra on a peak-to-peak basis, on a neutral loss-to-neutral loss basis, or by the m/z value and molecular formula, search chemical compounds by substructures, and keyword search chemical compounds

Proper citation: MassBank (RRID:SCR_015535) Copy   

•   Source: SciCrunch Registry