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http://www.vaccineinjury.info/vaccine-damage-reports-2010.html

Database of case reports of adverse reactions to vaccinations. There are 806 reports (May 2013). If you would like to report a case, please go to report your own vaccine reaction. The user may search by keywords or sort by vaccine, country, age, outcome, gender and hospital admission.

Proper citation: Vaccine damage reports database (RRID:SCR_010740) Copy   

•   Source: SciCrunch Registry

http://www.cs.tau.ac.il/~spike/

Database of curated human signaling pathways with an associated interactive software tool for analysis and dynamic visualization of pathways. Individual pathway maps can be viewed and downloaded; the entire database may be browsed, or launched via a map viewer tool that allows dynamic visualization of the database and save networks in XGMML format that can be viewed in all generic XGMML viewers. Map Topics * Cell cycle progress and check points * DNA damage response * Programmed cell death related processes * Stress-activated transcription factors * Mitogen-activated protein kinase pathways * Immune response signaling * HEarSpike: hearing related pathways

Proper citation: SPIKE (RRID:SCR_010466) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/atag/

This atlas takes advantage of ultra-high resolution 7T MRI to provide unprecedented levels of detail on structures of the basal ganglia in-vivo. The atlas includes probability maps of the Subthalamic Nucleus (STh) using T2*-imaging. For now it has been created on 13 young healthy participants with a mean age of 24.38 (range: 22-28, SD: 2.36). We recently also created atlas STh probability maps from 8 middle-aged participants with a mean age of 50.67 (range: 40-59, SD: 6.63), and 9 elderly participants with a mean age of 72.33 (range: 67-77, SD: 2.87). You can find more details about the creation of these maps in the following papers: Young: http://www.ncbi.nlm.nih.gov/pubmed/22227131 Middle-aged & Elderly: http://www.ncbi.nlm.nih.gov/pubmed/23486960 Participating institutions are the Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, and the Cognitive Science Center Amsterdam, University of Amsterdam, the Netherlands.

Proper citation: Atlasing of the basal ganglia (RRID:SCR_009431) Copy   

•   Source: SciCrunch Registry

http://gsgator.ewha.ac.kr/

A web-based platform for functional interpretation of gene sets with features such as cross-species Gene Set Analysis (GSA), Flexible and Interactive GSA, simultaneous GSA for multiple gene set, and and a fully integrated network viewer for both visualizing GSA results and molecular networks.

Proper citation: gsGator (RRID:SCR_012035) Copy   

•   Source: SciCrunch Registry

http://cbbiweb.uthscsa.edu/KMethylomes/

Datbase and web-based system for visualization and analysis of genome-wide methylation data of human cancers.

Proper citation: Cancer Methylome System (RRID:SCR_012013) Copy   

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http://appris.bioinfo.cnio.es/

A database that houses annotations of human splice isoforms. It adds reliable protein structural and functional data and information from cross-species conservation. A visual representation of the annotations for each gene allows users to easily identify functional changes brought about by splicing events. In addition to collecting, integrating and analyzing reliable predictions of the effect of splicing events, it also selects a single reference sequence for each gene, termed the principal isoform, based on the annotations of structure, function and conservation for each transcript.

Proper citation: APPRIS (RRID:SCR_012019) Copy   

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http://www.benoslab.pitt.edu/comir/

Data analysis service that predicts whether a given mRNA is targeted by a set of miRNAs. ComiR uses miRNA expression to improve and combine multiple miRNA targets for each of the four prediction algorithms: miRanda, PITA, TargetScan and mirSVR. The composite scores of the four algorithms are then combined using a support vector machine trained on Drosophila Ago1 IP data.

Proper citation: ComiR (RRID:SCR_013023) Copy   

•   Source: SciCrunch Registry

http://jbirc.jbic.or.jp/h-dbas/

A specialized database for human alternative splicing (AS) based on H-Invitational full-length cDNAs. H-DBAS offers unique data and viewer for human Alternative Splicing (AS) analysis. It contains: * Genome-wide representative alternative splicing variants (RASVs) identified from following datasets * H-Inv full-length cDNAs (resource summary): H-Invitational cDNA dataset * H-Inv all transcripts (resource summary): Published human mRNA dataset * Mouse full-length cDNAs (resource summary): Mouse cDNA dataset * RASVs affecting protein functions such as protein motif, GO, subcellular localization signal and transmembrane domain * Conserved RASVs compared with mouse genome and the full-length cDNAs (H-Inv full-length cDNAs only)

Proper citation: Human Transcriptome Database for Alternative Splicing (RRID:SCR_013305) Copy   

•   Source: SciCrunch Registry

http://bioinf.uta.fi/BTKbase/

A mutation registry for X-linked agammaglobulinemia (XLA). BTKbase lists mutation entries of 1,111 patients from 973 unrelated families showing 602 unique molecular events. Agammaglobulinemia is characterized by failure to produce mature B lymphocyte cells and is associated with a failure of Ig heavy chain rearrangement. Two thirds of cases are familial, and one third of cases are believed to arise from new mutations. Mutations of the BTK gene are found in approximately 80% of patients with agammaglobulinemia. The localization of the mutations on the gene and protein for BTK can be analyzed by clicking sequences on the web pages. It includes a mutation browser, which gives users access to mutations in Bruton tyrosine kinase (BTK) protein sequences, and XLA fact file, and forms for users to submit mutation to the dataset.

Proper citation: BTKbase (RRID:SCR_013101) Copy   

•   Source: SciCrunch Registry

http://dorina.mdc-berlin.de/rbp_browser/dorina.html

In animals, RNA binding proteins (RBPs) and microRNAs (miRNAs) post-transcriptionally regulate the expression of virtually all genes by binding to RNA. Recent advances in experimental and computational methods facilitate transcriptome-wide mapping of these interactions. It is thought that the combinatorial action of RBPs and miRNAs on target mRNAs form a post-transcriptional regulatory code. We provide a database that supports the quest for deciphering this regulatory code. Within doRiNA, we are systematically curating, storing and integrating binding site data for RBPs and miRNAs. Users are free to take a target (mRNA) or regulator (RBP and/or miRNA) centric view on the data. We have implemented a database framework with short query response times for complex searches (e.g. asking for all targets of a particular combination of regulators). All search results can be browsed, inspected and analyzed in conjunction with a huge selection of other genome-wide data, because our database is directly linked to a local copy of the UCSC genome browser. At the time of writing, doRiNA encompasses RBP data for the human, mouse and worm genomes. For computational miRNA target site predictions, we provide an update of PicTar predictions.

Proper citation: doRiNA (RRID:SCR_013222) Copy   

•   Source: SciCrunch Registry

http://agem.cnb.csic.es/VisualOmics/aGEM/

Database platform of an integrated view of eight databases (mouse gene expression resources: EMAGE, GXD, GENSAT, BioGPS, ABA, EUREXPRESS; human gene expression databases: HUDSEN, BioGPS and Human Protein Atlas) that allows the experimentalist to retrieve relevant statistical information relating gene expression, anatomical structure (space) and developmental stage (time). Moreover, general biological information from databases such as KEGG, OMIM and MTB is integrated too. It can be queried using gene and anatomical structure. Output information is presented in a friendly format, allowing the user to display expression maps and correlation matrices for a gene or structure during development. An in-depth study of a specific developmental stage is also possible using heatmaps that relate gene expression with anatomical components. This is a powerful tool in the gene expression field that makes easy the access to information related to the anatomical pattern of gene expression in human and mouse, so that it can complement many functional genomics studies. The platform allows the integration of gene expression data with spatial-temporal anatomic data by means of an intuitive and user friendly display., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: aGEM (RRID:SCR_013349) Copy   

•   Source: SciCrunch Registry

http://www.deathdomain.org/

A manually curated database of protein-protein interactions for Death Domain Superfamily. The Death Domain Database provides a detailed summary of PPI data, which fits into 3 categories: interaction, characterization, and functional role. Users can find in-depth information specified in the literature on relevant analytical methods, structural information. The DD superfamily currently comprises four subfamilies: * Death domain (DD) subfamily * Death effector domain (DED) subfamily * Caspase recruitment domain (CARD) subfamily * Pyrin domain (PYD) subfamily

Proper citation: Death Domain database (RRID:SCR_013231) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/cmap/

The Brain Coactivation Map describes all the coactivation networks in the human brain based on the meta-analysis of more than 5,400 neuroimaging articles (from NeuroSynth) containing more than 16,000 individual experiments. The map can be browsed interactively (CoactivationMap.app on GitHub) or queried from a shell using a command line tool (cmtool on GitHub).

Proper citation: Brain Coactivation Map (RRID:SCR_014172) Copy   

•   Source: SciCrunch Registry

http://db.systemsbiology.net/kaviar/

A database containing a compilation of SNVs, indels, and complex variants observed in humans, designed to facilitate testing for the novelty and frequency of observed variants.

Proper citation: KAVIAR (RRID:SCR_013737) Copy   

•   Source: SciCrunch Registry

http://gtlinker.cnb.csic.es/

Web application that filters and links enriched output data identifying sets of associated genes and terms, producing metagroups of coherent biological significance. The method uses fuzzy reciprocal linkage between genes and terms to unravel their functional convergence and associations. It can also be accessed through its web service.

Proper citation: GeneTerm Linker (RRID:SCR_006385) Copy   

•   Source: SciCrunch Registry

http://genetrail.bioinf.uni-sb.de/

A web-based application that analyzes gene sets for statistically significant accumulations of genes that belong to some functional category. Considered category types are: KEGG Pathways, TRANSPATH Pathways, TRANSFAC Transcription Factor, GeneOntology Categories, Genomic Localization, Protein-Protein Interactions, Coiled-coil domains, Granzyme-B clevage sites, and ELR/RGD motifs. The web server provides two statistical approaches, "Over-Representation Analysis" (ORA) comparing a reference set of genes to a test set, and "Gene Set Enrichment Analysis" (GSEA) scoring sorted lists of genes., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GeneTrail (RRID:SCR_006250) Copy   

•   Source: SciCrunch Registry

http://compbio.charite.de/phenomizer/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 31,2026. Phenomizer offers three different approaches to find the appropriate term for a phenotypic abnormality, indicated by the three tabs on the left hand side: Feature, Disease and Ontology. The Phenomizer is intended to be used by qualified and licensed physicians in order to provide assistance in reaching the correct diagnosis in patients with hereditary diseases and for use as a teaching aid. The Phenomizer does not make diagnoses. Rather, it produces a ranked list of possibilities that can be used by physicians as a part of the diagnostic workup. The Phenomizer does not contain information about all possible diagnoses or even all possible hereditary diseases. The Phenomizer should not be used to make medical decisions without the advice of a physician.

Proper citation: Phenomizer (RRID:SCR_006157) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry