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http://ercsb.ewha.ac.kr:8080/FusionGene/

Knowledgebase of fusion transcripts collected from various public resources such as the Sanger CGP, OMIM, PubMed, and Mitelman's database. It is an alignment viewer to facilitate examining reliability of fusion transcripts and inferring functional significance., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: ChimerDB (RRID:SCR_007596) Copy   

•   Source: SciCrunch Registry

https://omictools.com/ecgene-tool

Database of functional annotation for alternatively spliced genes. It uses a gene-modeling algorithm that combines the genome-based expressed sequence tag (EST) clustering and graph-theoretic transcript assembly procedures. It contains genome, mRNA, and EST sequence data, as well as a genome browser application. Organisms included in the database are human, dog, chicken, fruit fly, mouse, rhesus, rat, worm, and zebrafish. Annotation is provided for the whole transcriptome, not just the alternatively spliced genes. Several viewers and applications are provided that are useful for the analysis of the transcript structure and gene expression. The summary viewer shows the gene summary and the essence of other annotation programs. The genome browser and the transcript viewer are available for comparing the gene structure of splice variants. Changes in the functional domains by alternative splicing can be seen at a glance in the transcript viewer. Two unique ways of analyzing gene expression is also provided. The SAGE tags deduced from the assembled transcripts are used to delineate quantitative expression patterns from SAGE libraries available publicly. The cDNA libraries of EST sequences in each cluster are used to infer qualitative expression patterns.

Proper citation: ECgene: Gene Modeling with Alternative Splicing (RRID:SCR_007634) Copy   

•   Source: SciCrunch Registry

http://degradome.uniovi.es

A database of human, chimpanzee, mouse, and rat proteases and protease inhibitors, as well as as the growing number of hereditary diseases caused by mutations in protease genes. Analysis of the human and mouse genomes has allowed us to annotate 581 human, 580 chimpanzee, 667 mouse, and 655 rat protease genes. Proteases are classified in five different classes according to their mechanism of catalysis. Proteases are a diverse and important group of enzymes representing >2% of the human, chimpanzee, mouse and rat genomes. This group of enzymes is implicated in numerous physiological processes. The importance of proteases is illustrated by the existence of 99 different hereditary diseases due to mutations in protease genes. Furthermore, proteases have been implicated in multiple human pathologies, including vascular diseases, rheumatoid arthritis, neurodegenerative processes, and cancer. During the last ten years, our laboratory has identified and characterized more than 60 human protease genes. Due to the importance of proteolytic enzymes in human physiology and pathology, we have recently introduced the concept of Degradome, as the complete repertoire of proteases expressed by a tissue or organism. Thanks to the recent completion of the human, chimpanzee, mouse, and rat genome sequencing projects, we were able to analyze and compare for the first time the complete protease repertoire in those mammalian organisms, as well as the complement of protease inhibitor genes. This webpage also contains the Supplementary Material of Human and mouse proteases: a comparative genomic approach Nat Rev Genet (2003) 4: 544-558, Genome sequence of the brown Norway rat yields insights into mammalian evolution Nature (2004) 428: 493-521, A genomic analysis of rat proteases and protease inhibitors Genome Res. (2004) 14: 609-622, and Comparative genomic analysis of human and chimpanzee proteases Genomics (2005) 86: 638-647.

Proper citation: Mammalian Degradome Database (RRID:SCR_007624) Copy   

•   Source: SciCrunch Registry

http://www.mapuproteome.com

Database containing several body fluid proteomes, including plasma, urine, and cerebrospinal fluid. Cell lines have been mapped to a depth of several thousand proteins and the red blood cell proteome has also been analyzed in depth. The liver proteome is represented with 3200 proteins. By employing high resolution MS and stringent validation criteria, false positive identification rates in MAPU are lower than 1:1000. Thus MAPU datasets can serve as reference proteomes in biomarker discovery. MAPU contains the peptides identifying each protein, measured masses, scores and intensities using a clickable interface of cell or body parts. Proteome data can be queried across proteomes by protein name, accession number, sequence similarity, peptide sequence and annotation information. More than 4500 mouse and 2500 human proteins have already been identified in at least one proteome. Basic annotation information and links to other public databases are provided in MAPU and we plan to add further analysis tools.

Proper citation: Max Planck Unified Proteome Database (RRID:SCR_007771) Copy   

•   Source: SciCrunch Registry

http://text0.mib.man.ac.uk/software/mldic/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 9, 2022. System that retrieves relevant UniProt IDs from BioThesaurus entries using a soft string matching algorithm.

Proper citation: Smart Dictionary Lookup (RRID:SCR_000568) Copy   

•   Source: SciCrunch Registry

http://dgcst.ceinge.unina.it/

A database of conserved sequence elements, identified by a systematic genomic sequence comparison between a set of human genes involved in the pathogenesis of genetic disorders and their murine counterparts. Human and mouse genomic sequences were compared by BLASTZ. Sequences longer than 100 and with identity better than 70 were selected as CSTs and imported into the database. CSTs are extensively annotated with respect to exon/intron structure and other biological parameters. CST counterparts in other species were identified by using BLAST to scan genomes from other species, and selecting on the basis of homology and co-linearity. The database can be accessed by gene, chromosomal location, graphic browser, DNA features, and coding regions.

Proper citation: Disease Genes Conserved Sequence Tags Database (RRID:SCR_000760) Copy   

•   Source: SciCrunch Registry

http://mitominer.mrc-mbu.cam.ac.uk/

A database of mitochondrial proteomics data. It includes two sets of proteins: the MitoMiner Reference Set, which has 10477 proteins from 12 species; and MitoCarta, which has 2909 proteins from mouse and human mitochondrial proteins. MitoMiner provides annotation from the Gene Ontology (GO) and UniProt databases. This reference set contains all proteins that are annotated by either of these resources as mitochondrial in any of the species included in MitoMiner. MitoMiner data via is available via Application Programming Interface (API). The client libraries are provided in Perl, Python, Ruby and Java.

Proper citation: MitoMiner (RRID:SCR_001368) Copy   

•   Source: SciCrunch Registry

http://mus.well.ox.ac.uk/gscandb/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Database / display tool of genome scans, with a web interface that lets the user view the data. It does not perform any analyses - these must be done by other software, and the results uploaded into it. The basic features of GSCANDB are: * Parallel viewing of scans for multiple phenotypes. * Parallel analyses of the same scan data. * Genome-wide views of genome scans * Chromosomal region views, with zooming * Gene and SNP Annotation is shown at high zoom levels * Haplotype block structure viewing * The positions of known Trait Loci can be overlayed and queried. * Links to Ensembl, MGI, NCBI, UCSC and other genome data browsers. In GSCANDB, a genome scan has a wide definition, including not only the usual statistical genetic measures of association between genetic variation at a series of loci and variation in a phenotype, but any quantitative measure that varies along the genome. This includes for example competitive genome hybridization data and some kinds of gene expression measurements.

Proper citation: WTCHG Genome Scan Viewer (RRID:SCR_001635) Copy   

•   Source: SciCrunch Registry

http://bodymap.genes.nig.ac.jp/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 17, 2013. A taxonomical and anatomical database of latest cross species animal EST data, clustered by UniGene and inter connected by Inparanoid. Users can search by Unigene, RefSeq, or Entrez Gene ID, or search for Gene Name or Tissue type. Data is also sortable and viewable based on qualities of normal, Neoplastic, or other. The last data import appears to be from 2008

Proper citation: BodyMap-Xs (RRID:SCR_001147) Copy   

•   Source: SciCrunch Registry

http://mips.helmholtz-muenchen.de/genre/proj/corum

Database of manually annotated protein complexes from mammalian organisms. Annotation includes protein complex function, localization, subunit composition, literature references and more. All information is obtained from individual experiments published in scientific articles, but data from high-throughput experiments is excluded.
The majority of protein complexes in CORUM originates from man (65%), followed by mouse (14%) and rat (14%)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: CORUM (RRID:SCR_002254) Copy   

•   Source: SciCrunch Registry

http://brainvis.wustl.edu/wiki/index.php/Caret:Atlases

THIS RESOURCE IS NO LONGER IS SERVICE. Documented on July,29,2022. Surface-based atlases of human, macaque, rat and mouse cerebral and cerebellar cortices derived from structural MRI volumes developed in the Van Essen laboratory can be downloaded by direct links on the SumsDB database and can be viewed using freely available Caret (offline) and WebCaret (online) software. The human and macaque atlases include a large and growing compendium of experimental data pertaining to the structural and functional organization of primate cerebral cortex.

Proper citation: Surface-Based Atlases (RRID:SCR_002099) Copy   

•   Source: SciCrunch Registry

http://www.cisred.org/

Database for conserved sequence motifs identified by genome scale motif discovery, similarity, clustering, co-occurrence and coexpression calculations. Sequence inputs include low-coverage genome sequence data and ENCODE data. The database offers information on atomic motifs, motif groups and patterns. In promoter-based cisRED databases, sequence search regions for motif discovery extend from 1.5 Kb upstream to 200b downstream of a transcription start site, net of most types of repeats and of coding exons. Many transcription factor binding sites are located in such regions. For each target gene's search region, a base set of probabilistic ab initio discovery tools is used, in parallel, to find over-represented atomic motifs. Discovery methods use comparative genomics with over 40 vertebrate input genomes. In ChIP-seq-based cisRED databases, sequence search regions for motif discovery correspond to significant peaks that represent genome-wide sites of protein-DNA binding. Because such peaks occur in a wide range of genic and intergenic locations, ChIP-seq and promoter-based databases are complementary. Currently, motif discovery for ChIP-seq data uses scan-based approaches that make more explicit use of sets of sequences known to be functional transcription factor binding sites, and that consider a wide range of levels of conservation. For the human STAT1 ChIP-seq database search regions in the target species (human) was selected +/- 300 bp around the ChIP-seq peak maximum. Repeats and coding regions were masked. Multiple sequence alignment were used to assemble orthologous input sequences from other species.

Proper citation: cisRED: cis-regulatory element (RRID:SCR_002098) Copy   

•   Source: SciCrunch Registry

http://mpromdb.wistar.upenn.edu/

A curated database that strives to annotate gene promoters identified from ChIP-Seq experiment results. The long term goal of the database is to provide an integrated resource for mammalian gene transcriptional regulation and epigenetics. Users can search based on Enterz gene id/symbol, or by tissue/cell specific activity and filter results based on any combination of tissue/cell specificity, known/novel, CpG/NonCpG, and protein-coding/non-coding gene promoters. It is also integrated with GBrowse genome browser for visualiztion of ChIP-seq profiles and display the annotations.

Proper citation: MPromDb (RRID:SCR_002136) Copy   

•   Source: SciCrunch Registry

http://www.credrivermice.org/expression/

Database of microarray analysis of twelve major classes of fluorescent labeled neurons within the adult mouse forebrain that provide the first comprehensive view of gene expression differences. The publicly available datasets demonstrate a profound molecular heterogeneity among neuronal subtypes, represented disproportionately by gene paralogs, and begin to reveal the genetic programs underlying the fundamental divisions between neuronal classes including that between glutamatergic and GABAergic neurons. Five of the 12 populations were chosen from cingulate cortex and included several subtypes of GABAergic interneurons and pyramidal neurons. The remaining seven were derived from the somatosensory cortex, hippocampus, amygdala and thalamus. Using these expression profiles, they were able to construct a taxonomic tree that reflected the expected major relationships between these populations, such as the distinction between cortical interneurons and projection neurons. The taxonomic tree indicated highly heterogeneous gene expression even within a single region. This dataset should be useful for the classification of unknown neuronal subtypes, the investigation of specifically expressed genes and the genetic manipulation of specific neuronal circuit elements. Datasets: * Full: Here you can query gene expression results for the neuronal populations * Strain: Here you can query the same expression results accessed under the full checkbox, with one additional population (CT6-CG2) included as a control for the effects of mouse strain. This population is identical to CT6-CG (YFPH) except the neurons were derived from wild-type mice of three distinct strains: G42, G30, and GIN. * Arlotta: Here you can query the same expression results accessed under the full checkbox, with nine additional populations from the dataset of Arlotta et al., 2005. These populations were purified by FACS after retrograde labeling with fluorescent microspheres. Populations are designated by the prefix ACS for corticospinal neurons, ACC for corticocallosal neurons and ACT for corticotectal neurons, followed by the suffix E18 for gestational age 18 embryos, or P3, P6 and P14 for postnatal day 3, 6 and 14 pups. For each successful gene query the following information is returned: # Signal level line plot: Signal level is plotted on Y-axis (log base 2) for each sample. Samples include the thirty six representing the twelve populations profiled in Sugino et al. In addition, six samples from homogenized (=dissociated and but not sorted) cortex are included representing two different strains: G42-HO is homogenate from strain G42, GIN-HO is homogenate from stain GIN. # Signal level raster plots: Signal level is represented by color (dark red is low, bright red is high) for all samples. Color scale is set to match minimum (dark red) and maximum (bright yellow) signal levels within the displayed set of probe sets. # Scaled signal level raster plots: Same as 2) except color scale is adjusted separately for each gene according to its maximum and minimum signal level. # Table: Basic information about the returned probe sets: * Affymetrix affyid of probe set * NCBI gene symbol, NCBI gene name * NCBI geneID * P-value score from ANOVA for each gene is also given if available (_anv column). P-value represents the probability that there is no difference in the expression across cell types.

Proper citation: Mouse Neuronal Expression Database (RRID:SCR_002043) Copy   

•   Source: SciCrunch Registry

https://cell-innovation.nig.ac.jp/GNP/index_e.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Integrated database of experiment data generated by participating research institutes and public databases relating to: 1) transcription starting position of human genes in the human genome, 2) conjunction to control region on transcriptional factors and the human genome 3) protein-protein interaction with a central focus on transcription factors organized for use in genome level research. Gene Search is the function to search the integrated database by using keywords and public IDs. The search results can be visualized by: * Genome Explorer : provides annotation of landmarks (genes, transcription start sites, etc.) aligned in accordance with their genome locations. * PPI Network : provides a graphical view of protein-protein interaction (PPI) network from the experimental data generated under the project and the public datasets. * Expression Profile : clusters genes by expression pattern and display the result with heatmap. The function provides genes which have relation of coregulation and anti-coregulation. * Comparison Viewer : This function gives the view to compare the genomic regions between human and mouse homologous genes. The viewer shows the distribution of transcription start sites (TSS) as the way of separable by tissues or time points with other landmarks on genome region. * Gene Stock : This is the function to save the gene list that you are interested until the session is closed.

Proper citation: Genome Network Platform (RRID:SCR_001737) Copy   

•   Source: SciCrunch Registry

http://www.ariadnegenomics.com/products/databases/resnet/

Databases that represent sets of pre-compiled information on biological relationships and associations, interactions and facts which have been extracted from the biomedical literature using Ariadne's MedScan technology. ResNet databases store information harvested from the entire PubMed in a formal structure that allows searching, retrieval and updating by Pathway Studio user. ResNet is seamlessly installed when Pathway Studio is installed. There are several available ResNet databases: *ResNet Mammalian Database includes data for Human, Rat, and Mouse *ResNet Plant Database has data on Arabidopsis, Rice and several other plants. Features of ResNet: *All extracted relations have linked access to the original article or abstract *Synonyms and homologs are included to maintain gene identity and to obviate redundancy in search results *Users can update ResNet as often as required using the MedScan technology built into all Ariadne products *Updates are made available by Ariadne every quarter To purchase Pathway Studio software with ResNet database, for information, or to schedule a web demonstration, call our sales department at (240) 453-6272, or (866) 340-5040 (toll free)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: RESNET (RRID:SCR_002121) Copy   

•   Source: SciCrunch Registry

http://www.germonline.org/

Cross-species microarray expression database focusing on high-throughput expression data relevant for germline development, meiosis and gametogenesis as well as the mitotic cell cycle. The database contains a unique combination of information: 1) High-throughput expression data obtained with whole-genome high-density oligonucleotide microarrays (GeneChips). 2) Sample annotation (mouse over the sample name and click on it) using the Multiomics Information Management and Annotation System (MIMAS 3.0). 3) In vivo protein-DNA binding data and protein-protein interaction data (available for selected species). 4) Genome annotation information from Ensembl version 50. 5) Orthologs are identified using data from Ensembl and OMA and linked to each other via a section in the report pages. The portal provides access to the Saccharomyces Genomics Viewer (SGV) which facilitates online interpretation of complex data from experiments with high-density oligonucleotide tiling microarrays that cover the entire yeast genome. The database displays only expression data obtained with high-density oligonucleotide microarrays (GeneChips)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 15,2026.

Proper citation: GermOnline (RRID:SCR_002807) Copy   

•   Source: SciCrunch Registry

http://hollywood.mit.edu/hollywood/

Database built upon genomic annotation of splicing patterns of known genes derived from spliced alignment of complementary DNAs (cDNAs) and expressed sequence tags for human and mouse. It links features such as splice site sequence and strength, exonic splicing enhancers and silencers, conserved and non-conserved patterns of splicing, and cDNA library information for inferred alternative exons. A query tool allows searches for sets of exons with specific splicing characteristics or splicing regulatory element composition, or gives a graphical or sequence-level summary of splicing patterns for a specific gene. A graphical representation of gene splicing patterns is provided, and these patterns can alternatively be layered onto existing information in the UCSC Genome Browser.

Proper citation: Hollywood (RRID:SCR_002920) Copy   

•   Source: SciCrunch Registry

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

Automated system for constructing putative homology groups from complete gene sets of wide range of eukaryotic species. Databse that provides system for automatic detection of homologs, including paralogs and orthologs, among annotated genes of sequenced eukaryotic genomes. HomoloGene processing uses proteins from input organisms to compare and sequence homologs, mapping back to corresponding DNA sequences. Reports include homology and phenotype information drawn from Online Mendelian Inheritance in Man, Mouse Genome Informatics, Zebrafish Information Network, Saccharomyces Genome Database and FlyBase.

Proper citation: HomoloGene (RRID:SCR_002924) Copy   

•   Source: SciCrunch Registry

http://karg.cbi.pku.edu.cn

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 14,2026. Database of data and knowledge linking genes and chromosome regions to addiction that were extracted from reviewing more than 1,000 peer-reviewed publications from between 1976 and 2006. This list of publications included review papers on addiction selected from results of PUBMED query "(addiction OR drug abuse) AND review" as well as research papers selected from PUBMED query "(addiction OR drug abuse) AND (gene OR microarray OR proteomics OR QTL OR population association OR genetic linkage)". The data spanned multiple technology platforms including classical hypothesis-testing of single genes, identification of significantly differentially expressed genes in microarray experiments, identification of significantly differentially expressed proteins in proteomics assays, identification of addiction-vulnerable chromosome regions in animal QTL studies, genetic linkage studies, population association studies, and OMIM annotations. From each publication they collected the genes, proteins, or chromosome regions linked to addiction, as well as metadata such as species, nature of the addictive substance, studied brain regions, technology platforms, and experimental parameters. In total, they collected 2,343 items of evidence linking 1,500 human genes to addiction. Among them 396 genes were supported by two or more items of evidence. The interface supports browsing of the genes by chromosome or pathways, advanced text search by gene ID, organism, type of addictive substance, technology platform, protein domain, and/or PUBMED ID, and sequence search by BLAST similarity. All data, database schema, and MySQL commands are freely available for download.

Proper citation: Knowledgebase for Addiction Related Genes (RRID:SCR_002687) Copy   

•   Source: SciCrunch Registry