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https://www.embrys.jp/embrys/html/About.html

Data collection of gene expression patterns mapped in whole-mount mouse embryo (ICR strain) of mid-gestational stages (Embryonic Day 9.5, 10.5, 11.5), in which most striking dynamics in pattern formation and organogenesis is observed. Collection of gene expression patterns of transcription factors (TFs) and TF-related factors such as transcription cofactors. Genes were extracted from databases including RIKEN Transcription Factor Database and Panther Classification System.

Proper citation: EMBRYS (RRID:SCR_006689) Copy   

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

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. Database of sequence tagged sites (STSs) derived from STS-based maps and other experiments. STSs are defined by PCR primer pairs and are associated with additional information such as genomic position, genes, and sequences. Chromosome maps are labeled by name of the originating organism, the map title, total markers, total UniSTSs and links to view maps as well as research documents available through PubMed, another NCBI database. The search functions within UniSTS allow the user to search by gene marker, chromosome, gene symbol and gene description terms to locate markers on specified genes. A representation of the UniSTS datasets is available by ftp. NOTE: All data from this resource have been moved to the Probe database, http://www.ncbi.nlm.nih.gov/probe. You can retrieve all UniSTS records by searching the probe database using the search term unists(properties). (use brackets insead of parenthesis). Additionally, legacy data remain on the NCBI FTP Site in the UniSTS Repository (ftp://ftp.ncbi.nih.gov/pub/ProbeDB/legacy_unists).

Proper citation: UniSTS (RRID:SCR_006843) Copy   

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http://www.athamap.de/

Genome wide map of putative transcription factor binding sites in Arabidopsis thaliana genome.Data in AthaMap is based on published transcription factor (TF) binding specificities available as alignment matrices or experimentally determined single binding sites.Integrated transcriptional and post transcriptional data.Provides web tools for analysis and identification of co-regulated genes. Provides web tools for database assisted identification of combinatorial cis-regulatory elements and the display of highly conserved transcription factor binding sites in Arabidopsis thaliana.

Proper citation: AthaMap (RRID:SCR_006717) Copy   

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http://bond.unleashedinformatics.com/

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 August 19,2019.BOND, which requires registration of a free account, is a resource used to perform cross-database searches of available sequence, interaction, complex and pathway information. BOND integrates a range of component databases including GenBank and BIND, the Biomolecular Interaction Network Database. BOND contains 70+ million biological sequences, 33,000 structures, 38,000 GO terms, and over 200,000 human curated interactions contained in BIND, and is open access. BOND serves the interests of the developing global interactome effort encompassing the genomic, proteomic and metabolomic research communities. BOND is the first open access search resource to integrate sequence and interaction information. BOND integrates BLAST functionality, and contains a well-documented API. BOND also stores annotation links for sequences, including links to Genome Ontology descriptions, MedLine abstracts, taxon identifiers, associated structures, redundant sequences, sequence neighbors, conserved domains, data base cross-references, Online Mendalian Inheritance in Man identifiers, LocusLink identifiers and complete genomes. BIND on BOND The Biomolecular Interaction Network Database (BIND), a component database of BOND, is a collection of records documenting molecular interactions. The contents of BIND include high-throughput data submissions and hand-curated information gathered from the scientific literature. BIND is an interaction database with three classifications for molecular associations: molecules that associate with each other to form interactions, molecular complexes that are formed from one or more interaction(s) and pathways that are defined by a specific sequence of two or more interactions.Interactions A BIND record represents an interaction between two or more objects that is believed to occur in a living organism. A biological object can be a protein, DNA, RNA, ligand, molecular complex, gene, photon or an unclassified biological entity. BIND records are created for interactions which have been shown experimentally and published in at least one peer-reviewed journal. A record also references any papers with experimental evidence that support or dispute the associated interaction. Interactions are the basic units of BIND and can be linked together to form molecular complexes or pathways. The BIND interaction viewer is a tool to visualize and analyze molecular interactions, complexes and pathways. The BIND interaction viewer uses Ontoglyphs to display information about a protein via attributes such as molecular function, biological process and sub-cellular localization. Ontoglyphs allow to graphically and interactively explore interaction networks, by visualizing interactions in the context of 34 functional, 25 binding specificity and 24 sub-cellular localization Ontoglyphs categories. We will continue to provide an open access version of BOND, providing its subscribers with free, unlimited access to a core content set. But we are confident you will soon want to upgrade to BONDplus.

Proper citation: Biomolecular Object Network Databank (RRID:SCR_007433) Copy   

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http://ncrad.iu.edu/

Cell repository for Alzheimer's disease that collects and maintains biological specimens and associated data. Its data is derived from large numbers of genetically informative, phenotypically well-characterized families with multiple individuals affected with Alzheimer's disease, as well as individuals for case-control studies.

Proper citation: National Cell Repository for Alzheimer's Disease (RRID:SCR_007313) Copy   

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http://biobases.ibch.poznan.pl/5SData/

A database on nucleotide sequences of 5S rRNAs and their genes. The database contains 1985 primary structures of 5S rRNA and 5S rDNA, and was last updated in 2002, according to the website. They include 60 archaebacterial, 470 eubacterial, 63 plastid, nine mitochondrial and 1383 eukaryotic sequences. The nucleotide sequences of the 5S rRNAs or 5S rDNAs are divided according to the taxonomic position of the source organisms. The sequences for particular organisms can be retrieved as single files using a taxonomic browser or in multiple sequence structural alignments. The multiple sequence alignments of 5S ribosomal RNAs can be downloaded in TAB-delimited and FASTA formats.

Proper citation: 5S Ribosomal RNA Database (RRID:SCR_007545) Copy   

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http://mousespinal.brain-map.org/about.html

Platform for exploring spinal cord at cellular and molecular levels. Map of gene expression for adult and juvenile mouse spinal cord. Provides map of normal mouse when used to compare gene expression in diseased or injury models. Interactive database of gene expression mapped across all anatomic segments of mouse spinal cord at postnatal days 4 and 56. Indexed set of images based on RNA in situ hybridization data, searchable and sortable by gene, age, expression, cervical, thoracic, lumbar, sacral, and coccygeal segments.

Proper citation: Allen Mouse Spinal Cord Atlas (RRID:SCR_007418) Copy   

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http://mips.gsf.de/genre/proj/ustilago/

The MIPS Ustilago maydis Genome Database aims to present information on the molecular structure and functional network of the entirely sequenced, filamentous fungus Ustilago maydis. The underlying sequence is the initial release of the high quality draft sequence of the Broad Institute. The goal of the MIPS database is to provide a comprehensive genome database in the Genome Research Environment in parallel with other fungal genomes to enable in depth fungal comparative analysis. The specific aims are to: 1. Generate and assemble Whole Genome Shotgun sequence reads yielding 10X coverage of the U. maydis genome 2. Integrate the genomic sequence assembly with physical maps generated by Bayer CropScience 3. Perform automated annotation of the sequence assembly 4. Align the strain 521 assembly with the FB1 assembly provided by Exelixis 5. Release the sequence assembly and results of our annotation and analysis to public Ustilago maydis is a basidiomycete fungal pathogen of maize and teosinte. The genome size is approximately 20 Mb. The fungus induces tumors on host plants and forms masses of diploid teliospores. These spores germinate and form haploid meiotic products that can be propagated in culture as yeast-like cells. Haploid strains of opposite mating type fuse and form a filamentous, dikaryotic cell type that invades plant tissue to reinitiate infection. Ustilago maydis is an important model system for studying pathogen-host interactions and has been studied for more than 100 years by plant pathologists. Molecular genetic research with U. maydis focuses on recombination, the role of mating in pathogenesis, and signaling pathways that influence virulence. Recently, the fungus has emerged as an excellent experimental model for the molecular genetic analysis of phytopathogenesis, particularly in the characterization of infection-specific morphogenesis in response to signals from host plants. Ustilago maydis also serves as an important model for other basidiomycete plant pathogens that are more difficult to work with in the laboratory, such as the rust and bunt fungi. Genomic sequence of U. maydis will also be valuable for comparative analysis of other fungal genomes, especially with respect to understanding the host range of fungal phytopathogens. The analysis of U. maydis would provide a framework for studying the hundreds of other Ustilago species that attack important crops, such as barley, wheat, sorghum, and sugarcane. Comparisons would also be possible with other basidiomycete fungi, such as the important human pathogen C. neoformans. Commercially, U. maydis is an excellent model for the discovery of antifungal drugs. In addition, maize tumors caused by U. maydis are prized in Hispanic cuisine and there is interest in improving commercial production. The complete putative gene set of the Broad Institute''s second release is loaded into the database and in addition all deviating putative genes from a putative gene set produced by MIPS with different gene prediction parameters are also loaded. The complete dataset will then be analysed, gene predictions will be manually corrected due to combined information derived from different gene prediction algorithms and, more important, protein and EST comparisons. Gene prediction will be restricted to ORFs larger than 50 codons; smaller ORFs will be included only if similarities to other proteins or EST matches confirm their existence or if a coding region was postulated by all prediction programs used. The resulting proteins will be annotated. They will be classified according to the MIPS classification catalogue receiving appropriate descriptions. All proteins with a known, characterized homolog will be automatically assigned to functional categories using the MIPS functional catalog. All extracted proteins are in addition automatically analysed and annotated by the PEDANT suite.

Proper citation: MIPS Ustilago maydis Database (RRID:SCR_007563) Copy   

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http://www.homepages.ed.ac.uk/pmckeigu/pooling/poolscore.htm

Software program for analysis of case-control genetic association studies using allele frequency measurements on DNA pools (entry from Genetic Analysis Software)

Proper citation: POOLSCORE (RRID:SCR_007514) Copy   

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http://atlasgeneticsoncology.org/

Online journal and database devoted to genes, cytogenetics, and clinical entities in cancer, and cancer-prone diseases. Its aim is to cover the entire field under study and it presents concise and updated reviews (cards) or longer texts (deep insights) concerning topics in cancer research and genomics.

Proper citation: Atlas of Genetics and Cytogenetics in Oncology and Haematology (RRID:SCR_007199) Copy   

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http://www.ebi.ac.uk/GOA

An annotation program which aims to provide high-quality Gene Ontology (GO) annotations to proteins in the UniProt Knowledgebase (UniProtKB) and International Protein Index (IPI). It is a central dataset for other major multi-species databases, such as Ensembl and NCBI. Because of the multi-species nature of the UniProtKB, UniProtKB-GOA assists in the curation of 200,000 species. This involves electronic annotation and the integration of high-quality manual GO annotation from all GO Consortium model organism groups and specialist groups. Gene Association Files can be accessed from the Downloads section of the website.

Proper citation: GOA (RRID:SCR_007691) Copy   

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http://systers.molgen.mpg.de/

SYSTERS is a database of protein sequences grouped into homologous families and superfamilies. The SYSTERS project aims to provide a meaningful partitioning of the whole protein sequence space by a fully automatic procedure. A refined two-step algorithm assigns each protein to a family and a superfamily. The sequence data underlying SYSTERS release 4 now comprise several protein sequence databases derived from completely sequenced genomes (ENSEMBL, TAIR, SGD and GeneDB), in addition to the comprehensive Swiss-Prot/TrEMBL databases. To augment the automatically derived results, information from external databases like Pfam and Gene Ontology are added to the web server. Furthermore, users can retrieve pre-processed analyses of families like multiple alignments and phylogenetic trees. New query options comprise a batch retrieval tool for functional inference about families based on automatic keyword extraction from sequence annotations. A new access point, PhyloMatrix, allows the retrieval of phylogenetic profiles of SYSTERS families across organisms with completely sequenced genomes. Gene, Human, Vertebrate, Genome, Human ORFs

Proper citation: SYSTERS (RRID:SCR_007955) Copy   

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http://www.grt.kyushu-u.ac.jp/spad/

It is divided to four categories based on extracellular signal molecules (Growth factor, Cytokine, and Hormone) and stress, that initiate the intracellular signaling pathway. SPAD is compiled in order to describe information on interaction between protein and protein, protein and DNA as well as information on sequences of DNA and proteins. There are multiple signal transduction pathways: cascade of information from plasma membrane to nucleus in response to an extracellular stimulus in living organisms. Extracellular signal molecule binds specific intracellular receptor, and initiates the signaling pathway. Now, there is a large amount of information about the signaling pathway which controls the gene expression and cellular proliferation. We have developed an integrated database SPAD to understand the overview of signaling transduction.

Proper citation: Signaling Pathway Database (RRID:SCR_008243) Copy   

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http://interactome-cmp.ucsf.edu/

This database currently holds E-MAP scores (individual interactions and correlation coefficients) for budding yeast genes involved in the early secretory pathway and chromosome function (including DNA damage and repair, transcriptional control, chromosome segregation and telomere regulation). E-MAPs (Epistatic Mini Array Profiles) are formed by creating and quantifying high-density genetic interaction maps. With this method, observed double mutant colony sizes are compared to those that would be expected from a distribution of typical double mutant colonies of each strain. Each interaction is assigned a score, which indicates the magnitude of the difference from the expected value and the certainty of the score. Negative (or aggravating) scores (< -2.5) correspond to synthetic sick/lethal interactions while positive (or alleviating) scores (> +2.5) corresponds to epistatic or suppressor interactions.

Proper citation: Krogan Lab Interactome Database (RRID:SCR_008121) Copy   

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http://mrna.otago.ac.nz/

Database that provides access to mRNA sequences and associated regulatory elements that were processed from Genbank. These mRNA sequences include complete genomes, which are divided into 5-prime UTRs, 3-prime UTRs, initiation sequences, termination regions and full CDS sequences. This data can be searched for a range of properties including specific mRNA sequences, mRNA motifs, codon usage, RSCU values, information content, etc.

Proper citation: Transterm (RRID:SCR_008244) Copy   

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http://escience.invitrogen.com/ipath/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 26, 2016. LINNEA Pathways is a user-friendly comprehensive online resource for gene- or protein-based scientific research. It is based on a total of 248 signaling and metabolic human biological pathway maps created for Invitrogen by GeneGo. The current version of iPath features 225 maps displaying human regulatory and metabolic pathways established in experimental literature produced by MetaCore from GeneGo, Inc. The map objects (proteins, genes, EC functions, and compounds) are connected via metabolic transformations and physical protein interactions, which were assembled by the GeneGo team of experienced annotators, geneticists, and biochemists. The pathways are organized in a vertical fashion following the general signaling path from signaling molecules and membrane receptors, via signal transduction cascades, to transcription factors and their gene targets. Following the natural organization of cellular machinery with highly interconnected pathways and modules, many maps are linked together via hyperlinked box symbols. Such linkage allows the reconstruction of a big picture view of human cell biology., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Invitrogen iPath (RRID:SCR_008120) Copy   

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http://itfp.biosino.org/itfp/

ITFP is an integrated transcription factor (TF) platform, which included abundant TFs and targets message of mammalian. Support vector machine (SVM) algorithm combined with error-correcting output coding (ECOC) algorithm was utilized to identify and classify transcription factor from protein sequence of Human, Mouse and Rat. For transcription factor targets, a reverse engineering method named ARACNE was used to derive potential interaction pairs between transcription factor and downstream regulated gene from Human, Mouse and Rat gene expression profile data. Detailed information of gene expression profile data can be found in help page. Moreover, all data provided by the platform is free for non-commercial users and can be downloaded through links on help page.

Proper citation: Intergrated Transcription Factor Platform (RRID:SCR_008119) Copy   

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http://www.ingenuity.com/

A horizontally and vertically structured database that pulls scientific and medical information and describes it consistently using the Ingenuity Ontology. The Knowledge Base pulls information from journals, public molecular content databases, and textbooks. Data is curated and and integrated into the Knowledge Base .

Proper citation: Ingenuity Pathways Knowledge Base (RRID:SCR_008117) Copy   

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http://www.primervfx.com/#welcome

PrimerParadise is an online PCR primer database for genomics studies. The database contains predesigned PCR primers for amplification of exons, genes and SNPs of almost all sequenced genomes. Primers can be used for genome-wide projects (resequencing, mutation analysis, SNP detection etc). The primers for eukaryotic genomes have been tested with e-PCR to make sure that no alternative products will be generated. Also, all eukaryotic primers have been filtered to exclude primers that bind excessively throughout the genome. Genes are amplified as amplicons. Amplicons are defined as only one genes exons containing maximaly 3000 bp long dna segments. If gene is longer than 3000 bp then it is split into the segments at length 3000 bp. So for example gene at length 5000 bp is split into two segment and for both segments there were designed a separate primerpair. If genes exons length is over 3000 bp then it is split into amplicons as well. Every SNP has one primerpair. In addition of considering repetitive sequences and mono-dinucleotide repeats, we avoid designing primers to genome regions which contain other SNPs. -There are two ways to search for primers: you can use features IDs ( for SNP primers Reference ID, for gene/exon primers different IDs (Ensembl gene IDs, HUGO IDs for human genes, LocusLink IDs, RefSeq IDs, MIM IDs, NCBI gene names, SWISSPROT IDs for bacterial genes, VEGA gene IDs for human and mouse, Sanger S.pombe systematic gene names and common gene names, S.cerevisiae GeneBanks Locus, AccNo, GI IDs and common gene names) -you can use genome regions (chromosome coordinates, chromosome bands if exists) -Currently we provide 3 primers collections: proPCR for prokaryotic organisms genes primers -euPCR for eukaryotic organisms genes/exons primers -snpPCR for eukaryotic organisms SNP primers Sponsors: PrimerStudio is funded by the University of Tartu.

Proper citation: PrimerStudio (RRID:SCR_008232) Copy   

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http://microbialgenomics.energy.gov/index.shtml

Through its Microbial Genome Program (MGP) and its Genomics:GTL (GTL) program, DOEs Office of Biological and Environmental Research (BER) has sequenced more than 485 microbial genomes and 30 microbial communities having specialized biological capabilities. Identifying these genes will help investigators discern how gene activities in whole living systems are orchestrated to solve myriad life challenges. The MGP was begun in 1994 as a spinoff from the Human Genome Program. The goal of the program was to sequence the genomes of a number of nonpathogenic microbes that would be useful in solving DOE''s mission challenges in environmental-waste cleanup, energy production, carbon cycling, and biotechnology. Past projects include microbial genome program, microbial cell project, and the Laboratory Science Program at the DOE Joint Genome Institute. The two ongoing projects are Genomics: GTL program and Community Sequencing Program at the DOE Joint Genome Institute. Sponsors: Site sponsored by the U.S. Department of Energy Office of Science, Office of Biological and Environmental Research, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Microbial Genomics Program (RRID:SCR_008140) Copy   

•   Source: SciCrunch Registry