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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://machibase.gi.k.u-tokyo.ac.jp/

Database for Drosophila melanogaster transcription profiling that allows users to search the Drosophilia genome, see sequence overviews, and look at various transcripts. The data were generated in conjunction with the recently developed high-throughput genome sequencer Illumina / Solexa using a newly developed 5'-end mRNA collection method. Approximately 25 million 25-27 nucleotide (nt) 5'-end mRNA tags from the embryos, larvae, young males, young females, old males, old females, and S2 (culture cell line) of D. melanogaster were collected. By arranging this vast amount of expression tag with other annotated data, they have built a one-stop service for Drosophila melanogaster transcription profiling.

Proper citation: MachiBase (RRID:SCR_003078) 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   

•   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://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://scicrunch.org/resources

Portal providing identifiers for Antibodies, Model Organisms, and Tools (software, databases, services) created in support of the Resource Identification Initiative, which aims to promote research resource identification, discovery, and reuse. The portal offers a central location for obtaining and exploring Research Resource Identifiers (RRIDs) - persistent and unique identifiers for referencing a research resource. A critical goal of the RII is the widespread adoption of RRIDs to cite resources in the biomedical literature and other places that reference their generation or use. RRIDs use established community identifiers where they exist, and are cross-referenced in their system where more than one identifier exists for a single resource.

Proper citation: Resource Identification Portal (RRID:SCR_004098) Copy   

•   Source: SciCrunch Registry

http://llama.mshri.on.ca/funcassociate/

A web-based tool that accepts as input a list of genes, and returns a list of GO attributes that are over- (or under-) represented among the genes in the input list. Only those over- (or under-) representations that are statistically significant, after correcting for multiple hypotheses testing, are reported. Currently 37 organisms are supported. In addition to the input list of genes, users may specify a) whether this list should be regarded as ordered or unordered; b) the universe of genes to be considered by FuncAssociate; c) whether to report over-, or under-represented attributes, or both; and d) the p-value cutoff. A new version of FuncAssociate supports a wider range of naming schemes for input genes, and uses more frequently updated GO associations. However, some features of the original version, such as sorting by LOD or the option to see the gene-attribute table, are not yet implemented. Platform: Online tool

Proper citation: FuncAssociate: The Gene Set Functionator (RRID:SCR_005768) Copy   

•   Source: SciCrunch Registry

http://www.btool.org/ADGO2

A web-based tool that provides composite interpretations for microarray data comparing two sample groups as well as lists of genes from diverse sources of biological information. It provides multiple gene set analysis methods for microarray inputs as well as enrichment analyses for lists of genes. It screens redundant composite annotations when generating and prioritizing them. It also incorporates union and subtracted sets as well as intersection sets. Users can upload their gene sets (e.g. predicted miRNA targets) to generate and analyze new composite sets.

Proper citation: ADGO (RRID:SCR_006343) Copy   

•   Source: SciCrunch Registry

http://www.biocomputing.it/fidea/

A web server for the functional interpretation of differential expression analysis. It can: * Calculate overrepresentation statistics using KEGG, Interpro, Gene Ontology Molecular Function, Gene Ontology Biological Process, Gene Ontology Cellular Component and GoSlim classifications; * Analyze down-regulated and up-regulated DE genes separately or together as a single set; * Provide interactive graphs and tables that can be modified on the fly according to user defined parameters; the user can set a fold change filter and interactively see the effects on the gene set under examination; * Output publication-ready plot of the graph; * Compare the results of several experiments in any combination.

Proper citation: FIDEA (RRID:SCR_004187) Copy   

•   Source: SciCrunch Registry

http://signalink.org/

An integrated resource to analyze signaling pathway cross-talks, transcription factors, miRNAs and regulatory enzymes. The multi-layered database structure is made up of signaling pathways, their pathway regulators (e.g., scaffold and endocytotic proteins) and modifier enzymes (e.g., phosphatases, ubiquitin ligases), as well as transcriptional and post-transcriptional regulators of all of these components. The website allows the interactive exploration of how each signaling protein is regulated. Features * experimental data not only from humans but from two invertebrate model organisms, C. elegans and D. melanogaster; * combines manual curation with large-scale datasets; * provides confidence scores for each interaction; * operates a customizable download page with multiple file formats (e.g., BioPAX, Cytoscape, SBML).

Proper citation: SignaLink (RRID:SCR_003569) Copy   

•   Source: SciCrunch Registry

http://www.ihop-net.org/UniPub/iHOP/

Information system that provides a network of concurring genes and proteins extends through the scientific literature touching on phenotypes, pathologies and gene function. It provides this network as a natural way of accessing millions of PubMed abstracts. By using genes and proteins as hyperlinks between sentences and abstracts, the information in PubMed can be converted into one navigable resource, bringing all advantages of the internet to scientific literature research. Moreover, this literature network can be superimposed on experimental interaction data (e.g., yeast-two hybrid data from Drosophila melanogaster and Caenorhabditis elegans) to make possible a simultaneous analysis of new and existing knowledge. The network contains half a million sentences and 30,000 different genes from humans, mice, D. melanogaster, C. elegans, zebrafish, Arabidopsis thaliana, yeast and Escherichia coli.

Proper citation: Information Hyperlinked Over Proteins (RRID:SCR_004829) Copy   

•   Source: SciCrunch Registry

https://4dgenome.research.chop.edu/

Repository for chromatin interaction data. Records can be queried by genomic regions, gene names, organism, and detection technology. Database is continuously updated by curators. Contributions from scientific community.

Proper citation: 4D Genome (RRID:SCR_017489) Copy   

•   Source: SciCrunch Registry

http://flybrain.neurobio.arizona.edu/

An interactive database of the Drosophila melanogaster nervous system. It is used by the drosophila neuroscience community and by other researchers studying arthropod brain structure. Flybrain contains neuroanatomical peer reviewed descriptions of the central and peripheral nervous system of Drosophila melanogaster. It also contains an introductory hypertext tour guide to the basic structure of the nervous system, as well as more specific information concerning different anatomical structures, developmental stages, and visualization techniques for the Drosophila nervous system. Additionally, The site contains schematic representations, a 3D project, immunocytology stains, a library of golgi impregnations, and enhancer-trap images.

Proper citation: MIRROR: FlyBrain, An Online Atlas and Database of the Drosophila Nervous System (RRID:SCR_007661) Copy   

•   Source: SciCrunch Registry

http://organelledb.lsi.umich.edu/

Database of organelle proteins, and subcellular structures / complexes from compiled protein localization data from organisms spanning the eukaryotic kingdom. All data may be downloaded as a tab-delimited text file and new localization data (and localization images, etc) for any organism relevant to the data sets currently contained in Organelle DB is welcomed. The data sets in Organelle DB encompass 138 organisms with emphasis on the major model systems: S. cerevisiae, A. thaliana, D. melanogaster, C. elegans, M. musculus, and human proteins as well. In particular, Organelle DB is a central repository of yeast protein localization data, incorporating results from both previous and current (ongoing) large-scale studies of protein localization in Saccharomyces cerevisiae. In addition, we have manually curated several recent subcellular proteomic studies for incorporation in Organelle DB. In total, Organelle DB is a singular resource consolidating our knowledge of the protein composition of eukaryotic organelles and subcellular structures. When available, we have included terms from the Gene Ontologies: the cellular component, molecular function, and biological process fields are discussed more fully in GO. Additionally, when available, we have included fluorescent micrographs (principally of yeast cells) visualizing the described protein localization. Organelle View is a visualization tool for yeast protein localization. It is a visually engaging way for high school and undergraduate students to learn about genetics or for visually-inclined researchers to explore Organelle DB. By revealing the data through a colorful, dimensional model, we believe that different kinds of information will come to light.

Proper citation: Organelle DB (RRID:SCR_007837) Copy   

•   Source: SciCrunch Registry

http://www.microrna.org

Database of microRNA target predictions and expression profiles. Target predictions are based on a development of the miRanda algorithm which incorporates current biological knowledge on target rules and on the use of an up-to-date compendium of mammalian microRNAs. MicroRNA expression profiles are derived from a comprehensive sequencing project of a large set of mammalian tissues and cell lines of normal and disease origin. This website enables users to explore: * The set of genes that are potentially regulated by a particular microRNA. * The implied cooperativity of multiple microRNAs on a particular mRNA. * MicroRNA expression profiles in various mammalian tissues. The web resource provides users with functional information about the growing number of microRNAs and their interaction with target genes in many species and facilitates novel discoveries in microRNA gene regulation. The microRNA Target Detection Software, miRanda, is an algorithm for finding genomic targets for microRNAs. This algorithm has been written in C and is available as an open-source method under the GPL., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: microRNA.org (RRID:SCR_006997) Copy   

•   Source: SciCrunch Registry

https://neuinfo.org/about/sources/nlx_143622-1

International registry of biomaterial supply resources both for transplantation and research. Contributions to this resource are welcome. The database is searchable through NIF and is updated regularly.

Proper citation: One Mind Biospecimen Bank Listing (RRID:SCR_004193) Copy   

•   Source: SciCrunch Registry