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http://hint.yulab.org/

A database of high-quality protein-protein interactions in different organisms.

Proper citation: HINT (RRID:SCR_002762) Copy   

•   Source: SciCrunch Registry

http://dbtss.hgc.jp/

Database of transcriptional start sites (TSSs) representing exact positions in the genome based on a unique experimentally validated TSS sequencing method, TSS Seq. A major part of human adult and embryonic tissues are covered. DBTSS contains 491 million TSS tag sequences collected from a total of 20 tissues and 7 cell cultures. Also integrated is generated RNA-seq data of subcellular- fractionated RNAs and ChIP Seq data of histone modifications, RNA polymerase II and several transcriptional regulatory factors in cultured cell lines. Also included is external epigenomic data, such as chromatin map of the ENCODE project. They associated those TSS information with public and original SNV data, in order to identify single nucleotide variations (SNVs) in the regulatory regions.

Proper citation: DBTSS: Database of Transcriptional Start Sites (RRID:SCR_002354) Copy   

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http://geneseer.com/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 14,2026. Database to access gene information through common names and allows identification of homologs and paralogs for a given gene. This publicly available tool leverages public sequence data, gene metadata information, and other publicly available data to calculate and display orthologous and paralogous gene relationships for all genes from several species, including yeasts, insects, worms, vertebrates, mammals, and primates such as humans.

Proper citation: GeneSeer (RRID:SCR_002626) Copy   

•   Source: SciCrunch Registry

http://genome.ufl.edu/mapper/

A platform composed of three modules: the Database, the Search Engine, and rSNPs, for the computational identification of transcription factor binding sites (TFBSs) in multiple genomes, that combines TRANSFAC and JASPAR data with the search power of profile hidden Markov models (HMMs). The Database contains putative TFBSs found in the upstream sequences of genes from the human, mouse and D.melanogaster genomes. For each gene, they scanned the region from 10,000 base pairs upstream of the transcript start to 50 base pairs downstream of the coding sequence start against all their models. Therefore, the database contains putative binding sites in the gene promoter and in the initial introns and non-coding exons. Information displayed for each putative binding site includes the transcription factor name, its position (absolute on the chromosome, or relative to the gene), the score of the prediction, and the region of the gene the site belongs to. If the selected gene has homologs in any of the other two organisms, the program optionally displays the putative TFBSs in the homologs. The Search Engine allows the identification, visualization and selection of putative TFBSs occurring in the promoter or other regions of a gene from the human, mouse, D.melanogaster, C.elegans or S.cerevisiae genomes. In addition, it allows the user to upload a sequence to query and to build a model by supplying a multiple sequence alignment of binding sites for a transcription factor of interest. rSNPs MAPPER is designed to identify Single Nucleotide Polymorphisms (SNPs) that may have an effect on the presence of one or more TFBSs.

Proper citation: MAPPER - Multi-genome Analysis of Positions and Patterns of Elements of Regulation (RRID:SCR_003077) Copy   

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http://www.lipidmaps.org/data/proteome/LMPD.php

Database of lipid related proteins representing human and mouse proteins involved in lipid metabolism. Collection of lipid related genes and proteins contains data for genes and proteins from Homo sapiens, Mus musculus, Rattus norvegicus, Saccharomyces cerevisiae, Caenorhabditis elegans, Escherichia coli, Macaca mulata, Drosophila melanogaster, Arabidopsis thaliana and Danio rerio.

Proper citation: LIPID MAPS Proteome Database (RRID:SCR_003062) Copy   

•   Source: SciCrunch Registry

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

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 4, 2023. Database that provides special browsing capabilities for a subset of organisms in Entrez Genomes. Map Viewer allows users to view and search an organism's complete genome, display chromosome maps, and zoom into progressively greater levels of detail, down to the sequence data for a region of interest. If multiple maps are available for a chromosome, it displays them aligned to each other based on shared marker and gene names, and, for the sequence maps, based on a common sequence coordinate system.

Proper citation: MapViewer (RRID:SCR_003092) Copy   

•   Source: SciCrunch Registry

http://www.emouseatlas.org

Detailed multidimensional digital multimodal atlas of C57BL/6J mouse nervous system with data and informatics pipeline that can automatically register, annotate, and visualize large scale neuroanatomical and connectivity data produced in histology, neuronal tract tracing, MR imaging, and genetic labeling. MAP2.0 interoperates with commonly used publicly available databases to bring together brain architecture, gene expression, and imaging information into single, simple interface.Resource to visualise mouse development, identify anatomical structures, determine developmental stage, and investigate gene expression in mouse embryo. eMouseAtlas portal page allows access to EMA Anatomy Atlas of Mouse Development and EMAGE database of gene expression.EMAGE is freely available, curated database of gene expression patterns generated by in situ techniques in developing mouse embryo. EMA, e-Mouse Atlas, is 3-D anatomical atlas of mouse embryo development including histology and includes EMAP ontology of anatomical structure, provides information about shape, gross anatomy and detailed histological structure of mouse, and framework into which information about gene function can be mapped.

Proper citation: eMouseAtlas (RRID:SCR_002981) Copy   

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https://confluence.crbs.ucsd.edu/display/NIF/DRG

Gene expression data from published journal articles that test hypotheses relevant to neuroscience of addiction and addictive behavior. Data types include effects of particular drug, strain, or knock out on particular gene, in particular anatomical region. Focuses on gene expression data and exposes data from investigations using DNA microarrays, polymerase chain reaction, immunohistochemistry and in-situ hybridizations. Data are available for query through NIF interface.Data submissions are welcome.

Proper citation: Drug Related Gene Database (RRID:SCR_003330) Copy   

•   Source: SciCrunch Registry

http://biogps.org/

An extensible and customizable gene annotation portal that emphasizes community extensibility and user customizability. It is a complete resource for learning about gene and protein function. Community extensibility reflects a belief that any BioGPS user should be able to add new content to BioGPS using the simple plugin interface, completely independently of the core developer team. User customizability recognizes that not all users are interested in the same set of gene annotation data, so the gene report layouts enable each user to define the information that is most relevant to them. Currently, BioGPS supports eight species: Human (Homo sapiens), Mouse (Mus musculus), Rat (Rattus norvegicus), Fruitfly (Drosophila melanogaster), Nematode (Caenorhabditis elegans), Zebrafish (Danio rerio), Thale-cress (Arabidopsis thaliana), Frog (Xenopus tropicalis), and Pig (Sus scrofa). BioGPS presents data in an ortholog-centric format, which allows users to display mouse plugins next to human ones. Our data for defining orthologs comes from NCBI's HomoloGene database.

Proper citation: BioGPS: The Gene Portal Hub (RRID:SCR_006433) Copy   

•   Source: SciCrunch Registry

http://wavi.bioinfo.cnio.es/

A versatile web-server application for the analysis and visualization of array-CGH data.

Proper citation: waviCGH (RRID:SCR_006662) Copy   

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http://crcview.hegroup.org/

Web-based microarray data analysis and visualization system powered by CRC, or Chinese Restaurant cluster, a Dirichlet process model-based clustering algorithm recently developed by Dr. Steve Qin. It also incorporates several gene expression analysis programs from Bioconductor, including GOStats, genefilter, and Heatplus. CRCView also installs from the Bioconductor system 78 annotation libraries of microarray chips for human (31), mouse (24), rat (14), zebrafish (1), chicken (1), Drosophila (3), Arabidopsis (2), Caenorhabditis elegans (1), and Xenopus Laevis (1). CRCView allows flexible input data format, automated model-based CRC clustering analysis, rich graphical illustration, and integrated Gene Ontology (GO)-based gene enrichment for efficient annotation and interpretation of clustering results. CRC has the following features comparing to other clustering tools: 1) able to infer number of clusters, 2) able to cluster genes displaying time-shifted and/or inverted correlations, 3) able to tolerate missing genotype data and 4) provide confidence measure for clusters generated. You need to register for an account in the system to store your data and analyses. The data and results can be visited again anytime you log in.

Proper citation: CRCView (RRID:SCR_007092) Copy   

•   Source: SciCrunch Registry

http://www.mbl.org/mbl_main/atlas.html

High-resolution electronic atlases for mouse strains c57bl/6j, a/j, and dba/2j in either coronal or horizontal section. About this Atlas: The anterior-posterior coordinates are taken from an excellent print atlas of a C57BL/6J brain by K. Franklin and G. Paxinos (The Mouse Brain in Stereotaxic Coordinates, Academic Press, San Diego, 1997, ISBN Number 0-12-26607-6; Library of Congress: QL937.F72). The abbreviations we have used to label the sections conform to those in the Franklin-Paxinos atlas. A C57BL/6J mouse brain may contain as many as 75 million neurons, 23 million glial cells, 7 million endothelial cells associated with blood vessels, and 3 to 4 million miscellaneous pial, ependymal, and choroid plexus cells (see data analysis in Williams, 2000). We have not yet counted total cell number in DBA/2J mice, but the counts are probably appreciably lower.The brain and sections were all processed as described in our methods section. The enlarged images have a pixel count of 1865 x 1400 and the resolution is 4.5 microns/pixel for the processed sections.Plans: In the next several years we hope to add several additional atlases of the same sort for other strains of mice. A horizontal C57BL/6J atlas and a DBA/2J coronal atlas were completed by Tony Capra, summer 2000, and additional atlases may be made over the next several years. As describe in the MBL Procedures Section is not hard to make your own strain-specific atlas from the high resolution images in the MBL.

Proper citation: Mouse Brain Atlases (RRID:SCR_007127) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/genome/guide/mouse/MouseTranscriptome.html

Focus is the generation of a reference expression database for the C57BL/6J mouse. The current dataset will consist of 90 samples, primarily from adult tissue, and was analyzed using a technique known as Massively Parallel Signature Sequencing (MPSS). The data are stored in the Gene Expression Omnibus (GEO).The focus of this project is the generation of a reference RNA transcriptome expression database for the C57BL/6J mouse. The current dataset will consist of 90 samples, primarily from adult tissue, and was analyzed using a technique known as Massively Parallel Signature Sequencing (MPSS)

Proper citation: Mouse Transcriptome Project (RRID:SCR_007311) Copy   

•   Source: SciCrunch Registry

http://pepr.cnmcresearch.org/

An experiment in web-database access to large multi-dimensional data sets using a standardized experimental platform to determine if the larger scientific community can be given simple, intuitive, and user-friendly web-based access to large microarray data sets. All data in PEPR is also available via NCBI GEO. The structure and goals of PEPR differ from other mRNA expression profiling databases in a number of important ways. * The experimental platform in PEPR is standardized, and is an Affymetrix - only database. All microarrays available in the PEPR web database should ascribe to quality control and standard operating procedures. A recent publication has described the QC/SOP criteria utilized in PEPR profiles ( The Tumor Analysis Best Practices Working Group 2004 ). * PEPR permits gene-based queries of large Affymetrix array data sets without any specialized software. For example, a number of large time series projects are available within PEPR, containing 40-60 microarrays, yet these can be simply queried via a dynamic web interface with no prior knowledge of microarray data analysis. * Projects in PEPR originate from scientists world-wide, but all data has been generated by the Research Center for Genetic Medicine, Children''''s National Medical Center, Washington DC. Future developments of PEPR will allow remote entry of Affymetrix data ascribing to the same QC/SOP protocols. They have previously described an initial implementation of PEPR, and a dynamic web-queried time series graphical interface ( Chen et al. 2004 ). A publication showing the utility of PEPR for pharmacodynamic data has recently been published ( Almon et al. 2003 ).

Proper citation: Public Expression Profiling Resource (RRID:SCR_007274) Copy   

•   Source: SciCrunch Registry

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://www.geneatlas.org/gene/main.jsp

This website allows visitors to search for genes of interest based on their spatial expression patterns in the Postnatal Day 7 mouse brain. Geneatlas provides two searching tools: A graphical interface for customized spatial queries; A textual interface for querying annotated structures. Geneatlas is the product of a collaboration between researchers at Baylor College of Medicine, Rice University, and University of Houston.

Proper citation: Gene Atlas (RRID:SCR_008089) Copy   

•   Source: SciCrunch Registry

http://mouseatlas.caltech.edu/

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone.. Documented on October, 01, 2019.
3D digital atlas of normal mouse development constructed from magnetic resonance image data. The download is a zipped file containing the six atlases Theiler Stages (ts) 13, 21,23, 24, 25 and 26 and MRI data for an unlabeled ts19 embryo. To view the atlases, download and install MBAT from: http://mbat.loni.ucla.edu Specimens were prepared in aqueous, isotonic solutions to avoid tissue shrinkage. Limited specimen handling minimized physical perturbation of the embryos to ensure accurate geometric representations of developing mouse anatomy. Currently, the atlas contains orthogonal sections through MRI volumes, three stages of embryos that have annotated anatomy, photographs of several stages of development, lineage trees for annotated embryos and a gallery of images and movies derived from the annotations. Anatomical annotations can be viewed by selecting a transverse section and selecting a pixel on the displayed slice.

Proper citation: 3D MRI Atlas of Mouse Development (RRID:SCR_008090) Copy   

•   Source: SciCrunch Registry