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http://www.rcsb.org/#Category-welcome

Collection of structural data of biological macromolecules. Database of information about 3D structures of large biological molecules, including proteins and nucleic acids. Users can perform queries on data and analyze and visualize results.

Proper citation: Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) (RRID:SCR_012820) Copy   

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http://gmod.org/wiki/Flash_GViewer

Flash GViewer is a customizable Flash movie that can be easily inserted into a web page to display each chromosome in a genome along with the locations of individual features on the chromosomes. It is intended to provide an overview of the genomic locations of a specific set of features - eg. genes and QTLs associated with a specific phenotype, etc. rather than as a way to view all features on the genome. The features can hyperlink out to a detail page to enable to GViewer to be used as a navigation tool. In addition the bands on the chromosomes can link to defineable URL and new region selection sliders can be used to select a specific chromosome region and then link out to a genome browser for higher resolution information. Genome maps for Rat, Mouse, Human and C. elegans are provided but other genome maps can be easily created. Annotation data can be provided as static text files or produced as XML via server scripts. This tool is not GO-specific, but was built for the purpose of viewing GO annotation data. Platform: Online tool

Proper citation: Flash Gviewer (RRID:SCR_012870) Copy   

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http://mitobreak.portugene.com/cgi-bin/Mitobreak_home.cgi

Database with curated datasets of mitochondrial DNA (mtDNA) rearrangements. Users may submit new mtDNA rearrangements.

Proper citation: MitoBreak (RRID:SCR_012949) Copy   

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http://purl.bioontology.org/ontology/EMAP

A structured controlled vocabulary of stage-specific anatomical structures of the mouse (Mus).

Proper citation: Mouse Gross Anatomy and Development Ontology (RRID:SCR_003891) Copy   

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http://purl.bioontology.org/ontology/MPATH

A structured controlled vocabulary of mutant and transgenic mouse pathology phenotypes

Proper citation: Mouse Pathology Ontology (RRID:SCR_003950) Copy   

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http://www.epo-berlin.com/

A small and medium-sized enterprise (SME) that has expertise in preclinical pharmacology, pharmacokinetics, and toxicology for the characterization of novel anticancer therapeutics and predictive biomarkers like: cytostatics, biologicals (peptides, antibodies), (anti)-hormones, immunomodulators (cytokines), and gene therapeutics. EPO has modern laboratories licensed for animal experiments and gene technology (S2) and a broad panel of murine and human tumor models growing in immunocompetent (SPF-quality, syngeneic strains) or immunodeficient mice (nude, SCID, NOD/SCID). EPO has established imaging technologies to monitor in vivo tumor growth.

Proper citation: Experimental Pharmacology and Oncology Berlin-Buch (RRID:SCR_003954) Copy   

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http://www.phenosys.com/

A research- and development-oriented company based in Berlin that engineers and markets technology for animal behavior research offering unique, automated instrumentation. This includes specialized applications of virtual reality and touch screen technology for animal behavior environments and RFID (transponder) operated devices in home cage environments. Their experimental systems are used for behavioral phenotyping, brain research, experimental psychology, and the diagnostic characterization of animal models for translational medicine.

Proper citation: PhenoSys (RRID:SCR_004072) Copy   

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http://brainarchitecture.org/

Evolving portal that will provide interactive tools and resources to allow researchers, clinicians, and students to discover, analyze, and visualize what is known about the brain's organization, and what the evidence is for that knowledge. This project has a current experimental focus: creating the first brainwide mesoscopic connectivity diagram in the mouse. Related efforts for the human brain currently focus on literature mining and an Online Brain Atlas Reconciliation Tool. The primary goal of the Brain Architecture Project is to assemble available knowledge about the structure of the nervous system, with an ultimate emphasis on the human CNS. Such information is currently scattered in research articles, textbooks, electronic databases and datasets, and even as samples on laboratory shelves. Pooling the knowledge across these heterogeneous materials - even simply getting to know what we know - is a complex challenge that requires an interdisciplinary approach and the contributions and support of the greater community. Their approach can be divided into 4 major thrusts: * Literature Curation and Text Mining * Computational Analysis * Resource Development * Experimental Efforts

Proper citation: Brain Architecture Project (RRID:SCR_004283) Copy   

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http://openconnectomeproject.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 9, 2023. Connectomes repository to facilitate the analysis of connectome data by providing a unified front for connectomics research. With a focus on Electron Microscopy (EM) data and various forms of Magnetic Resonance (MR) data, the project aims to make state-of-the-art neuroscience open to anybody with computer access, regardless of knowledge, training, background, etc. Open science means open to view, play, analyze, contribute, anything. Access to high resolution neuroanatomical images that can be used to explore connectomes and programmatic access to this data for human and machine annotation are provided, with a long-term goal of reconstructing the neural circuits comprising an entire brain. This project aims to bring the most state-of-the-art scientific data in the world to the hands of anybody with internet access, so collectively, we can begin to unravel connectomes. Services: * Data Hosting - Their Bruster (brain-cluster) is large enough to store nearly any modern connectome data set. Contact them to make your data available to others for any purpose, including gaining access to state-of-the-art analysis and machine vision pipelines. * Web Viewing - Collaborative Annotation Toolkit for Massive Amounts of Image Data (CATMAID) is designed to navigate, share and collaboratively annotate massive image data sets of biological specimens. The interface is inspired by Google Maps, enhanced to allow the exploration of 3D image data. View the fork of the code or go directly to view the data. * Volume Cutout Service - RESTful API that enables you to select any arbitrary volume of the 3d database (3ddb), and receive a link to download an HDF5 file (for matlab, C, C++, or C#) or a NumPy pickle (for python). Use some other programming language? Just let them know. * Annotation Database - Spatially co-registered volumetric annotations are compactly stored for efficient queries such as: find all synapses, or which neurons synapse onto this one. Create your own annotations or browse others. *Sample Downloads - In addition to being able to select arbitrary downloads from the datasets, they have also collected a few choice volumes of interest. * Volume Viewer - A web and GPU enabled stand-alone app for viewing volumes at arbitrary cutting planes and zoom levels. The code and program can be downloaded. * Machine Vision Pipeline - They are building a machine vision pipeline that pulls volumes from the 3ddb and outputs neural circuits. - a work in progress. As soon as we have a stable version, it will be released. * Mr. Cap - The Magnetic Resonance Connectome Automated Pipeline (Mr. Cap) is built on JIST/MIPAV for high-throughput estimation of connectomes from diffusion and structural imaging data. * Graph Invariant Computation - Upload your graphs or streamlines, and download some invariants. * iPad App - WholeSlide is an iPad app that accesses utilizes our open data and API to serve images on the go.

Proper citation: Open Connectome Project (RRID:SCR_004232) Copy   

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http://variant.bioinfo.cipf.es/

Analysis tool that can report the functional properties of any variant in all the human, mouse or rat genes (and soon new model organisms will be added) and the corresponding neighborhoods. Also other non-coding extra-genic regions, such as miRNAs are included in the analysis. It not only reports the obvious functional effects in the coding regions but also analyzes noncoding SNVs situated both within the gene and in the neighborhood that could affect different regulatory motifs, splicing signals, and other structural elements. These include: Jaspar regulatory motifs, miRNA targets, splice sites, exonic splicing silencers, calculations of selective pressures on the particular polymorphic positions, etc. Software analysis pipelines used in the analysis of NGS data are highly modular, heterogeneous, and rapidly evolving. VARIANT can easily be incorporated into a NGS resequencing pipeline either as a CLI or invoked a webservice. It inputs data directly from the most widely used programs for SNV detection., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: VARIANT (RRID:SCR_005194) Copy   

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http://seqant.genetics.emory.edu/

A free web service and open source software package that performs rapid, automated annotation of DNA sequence variants (single base mutations, insertions, deletions) discovered with any sequencing platform. Variant sites are characterized with respect to their functional type (Silent, Replacement, 5' UTR, 3' UTR, Intronic, Intergenic), whether they have been previously submitted to dbSNP, and their evolutionary conservation. Annotated variants can be viewed directly on the web browser, downloaded in a tab delimited text file, or directly uploaded in a Browser Extended Data (BED) format to the UCSC genome browser. SeqAnt further identifies all loci harboring two or more coding sequence variants that help investigators identify potential compound heterozygous loci within exome sequencing experiments. In total, SeqAnt resolves a significant bottleneck by allowing an investigator to rapidly prioritize the functional analysis of those variants of interest.

Proper citation: SeqAnt (RRID:SCR_005186) Copy   

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http://bejerano.stanford.edu/prism/public/html/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PRISM (Stanford database) (RRID:SCR_005375) Copy   

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http://services.nbic.nl/copub/portal/

Text mining tool that detects co-occuring biomedical concepts in abstracts from the MedLine literature database. It allows batch input of multiple human, mouse or rat genes and produces lists of keywords from several biomedical thesauri that are significantly correlated with the set of input genes. These lists link to Medline abstracts in which the co-occurring input genes and correlated keywords are highlighted. Furthermore, CoPub can graphically visualize differentially expressed genes and over-represented keywords in a network, providing detailed insight in the relationships between genes and keywords, and revealing the most influential genes as highly connected hubs.

Proper citation: CoPub (RRID:SCR_005327) Copy   

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http://www.gene-regulation.com/pub/databases.html#transpath

Database on eukaryotic transcription factors, their experimentally-proven binding sites, consensus binding sequences (positional weight matrices) and regulated genes. Its broad compilation of binding sites allows the derivation of positional weight matrices. It can either be used as an encyclopedia, for both specific and general information on signal transduction, or can serve as a network analyzer. Cross-references to important sequence and signature databases such as EMBL/GenBank UniProt/Swiss-Prot InterPro or Ensembl EntrezGene RefSeq are provided. The database is equipped with the tools for data visualization and analysis. It has three modules: the first one is the data, which have been manually extracted, mostly from the primary literature; the second is PathwayBuilder, which provides several different types of network visualization and hence facilitates understanding; the third is ArrayAnalyzer, which is particularly suited to gene expression array interpretation, and is able to identify key molecules within signalling networks (potential drug targets). These key molecules could be responsible for the coordinated regulation of downstream events. Manual data extraction focuses on direct reactions between signalling molecules and the experimental evidence for them, including species of genes/proteins used in individual experiments, experimental systems, materials and methods. This combination of materials and methods is used in TRANSPATH to assign a quality value to each experimentally proven reaction, which reflects the probability that this reaction would happen under physiological conditions. Another important feature in TRANSPATH is the inclusion of transcription factor-gene relations, which are transferred from TRANSFAC, a database focused on transcription regulation and transcription factors. Since interactions between molecules are mainly direct, this allows a complete and stepwise pathway reconstruction from ligands to regulated genes.

Proper citation: TRANSPATH (RRID:SCR_005640) Copy   

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http://genemania.org/

Data analysis service to predict the function of your favorite genes and gene sets. Indexing 1,421 association networks containing 266,984,699 interactions mapped to 155,238 genes from 7 organisms. GeneMANIA interaction networks are available for download in plain text format. GeneMANIA finds other genes that are related to a set of input genes, using a very large set of functional association data. Association data include protein and genetic interactions, pathways, co-expression, co-localization and protein domain similarity. You can use GeneMANIA to find new members of a pathway or complex, find additional genes you may have missed in your screen or find new genes with a specific function, such as protein kinases. Your question is defined by the set of genes you input. If members of your gene list make up a protein complex, GeneMANIA will return more potential members of the protein complex. If you enter a gene list, GeneMANIA will return connections between your genes, within the selected datasets. GeneMANIA suggests annotations for genes based on Gene Ontology term enrichment of highly interacting genes with the gene of interest. GeneMANIA is also a gene recommendation system. GeneMANIA is also accessible via a Cytoscape plugin, designed for power users. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: GeneMANIA (RRID:SCR_005709) Copy   

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http://llama.mshri.on.ca/gofish/GoFishWelcome.html

Software program, available as a Java applet online or to download, allows the user to select a subset of Gene Ontology (GO) attributes, and ranks genes according to the probability of having all those attributes., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GoFish (RRID:SCR_005682) Copy   

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http://brainstars.org

BrainStars (or B*) is a quantitative expression database of the adult mouse brain. The database has genome-wide expression profile at 51 adult mouse CNS regions. For 51 CNS regions, slices (0.5-mm thick) of mouse brain were cut on a Mouse Brain Matrix, frozen, and the specific regions were punched out bilaterally with a microdissecting needle (gauge 0.5 mm) under a stereomicroscope. For each region, we took samples every 4 hours, starting at ZT0 (Zeitgaber time 0; the time of lights on), for 24 hours (6 time-point samples for each region), and we pooled the samples from the different time points. We independently sampled each region twice (n=2). These samples were purified their RNA, and measured with Affymetrix GeneChip Mouse Genome 430 2.0 arrays. Expression values were then summarized with the RMA method. After several analysis with the expression data, the data and analysis results were stored in the BrainStars database. The database has a REST-like Web API interface for accessing from your Web applications. This document shows how to access the database via our Web API.

Proper citation: BrainStars (RRID:SCR_005810) Copy   

•   Source: SciCrunch Registry

http://great.stanford.edu/public/html/splash.php

Data analysis service that predicts functions of cis-regulatory regions identified by localized measurements of DNA binding events across an entire genome. Whereas previous methods took into account only binding proximal to genes, GREAT is able to properly incorporate distal binding sites and control for false positives using a binomial test over the input genomic regions. GREAT incorporates annotations from 20 ontologies and is available as a web application. The utility of GREAT extends to data generated for transcription-associated factors, open chromatin, localized epigenomic markers and similar functional data sets, and comparative genomics sets. Platform: Online tool

Proper citation: GREAT: Genomic Regions Enrichment of Annotations Tool (RRID:SCR_005807) Copy   

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http://abgent.com

Antibody supplier.

Proper citation: Abgent (RRID:SCR_008393) Copy   

•   Source: SciCrunch Registry

http://www.textpresso.org/

An information extracting and processing package for biological literature that can be used online or installed locally via a downloadable software package, http://www.textpresso.org/downloads.html Textpresso's two major elements are (1) access to full text, so that entire articles can be searched, and (2) introduction of categories of biological concepts and classes that relate two objects (e.g., association, regulation, etc.) or describe one (e.g., methods, etc). A search engine enables the user to search for one or a combination of these categories and/or keywords within an entire literature. The Textpresso project serves the biological and biomedical research community by providing: * Full text literature searches of model organism research and subject-specific articles at individual sites. Major elements of these search engines are (1) access to full text, so that the entire content of articles can be searched, and (2) search capabilities using categories of biological concepts and classes that relate two objects (e.g., association, regulation, etc.) or identify one (e.g., cell, gene, allele, etc). The search engines are flexible, enabling users to query the entire literature using keywords, one or more categories or a combination of keywords and categories. * Text classification and mining of biomedical literature for database curation. They help database curators to identify and extract biological entities and facts from the full text of research articles. Examples of entity identification and extraction include new allele and gene names and human disease gene orthologs; examples of fact identification and extraction include sentence retrieval for curating gene-gene regulation, Gene Ontology (GO) cellular components and GO molecular function annotations. In addition they classify papers according to curation needs. They employ a variety of methods such as hidden Markov models, support vector machines, conditional random fields and pattern matches. Our collaborators include WormBase, FlyBase, SGD, TAIR, dictyBase and the Neuroscience Information Framework. They are looking forward to collaborating with more model organism databases and projects. * Linking biological entities in PDF and online journal articles to online databases. They have established a journal article mark-up pipeline that links select content of Genetics journal articles to model organism databases such as WormBase and SGD. The entity markup pipeline links over nine classes of objects including genes, proteins, alleles, phenotypes, and anatomical terms to the appropriate page at each database. The first article published with online and PDF-embedded hyperlinks to WormBase appeared in the September 2009 issue of Genetics. As of January 2011, we have processed around 70 articles, to be continued indefinitely. Extension of this pipeline to other journals and model organism databases is planned. Textpresso is useful as a search engine for researchers as well as a curation tool. It was developed as a part of WormBase and is used extensively by C. elegans curators. Textpresso has currently been implemented for 24 different literatures, among them Neuroscience, and can readily be extended to other corpora of text.

Proper citation: Textpresso (RRID:SCR_008737) Copy   

•   Source: SciCrunch Registry