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http://tcag.ca/index.html

Service and training support for academic, government, and private sector scientists worldwide in genomics, including laboratory experimentation, statistical analysis, and comprehensive bioinformatics support, including large-scale genome comparisons, algorithm and tools development, and database curation, annotation and hosting. The Centre for Applied Genomics hosts a variety of databases related to ongoing supported projects: *Autism Chromosome Rearrangement Database *Cystic Fibrosis Mutation Database *The Lafora Progressive Myoclonus Epilepsy Mutation and Polymorphism Database *Database of Genomic Variants *The Chromosome 7 Annotation Project *Human Genome Segmental Duplication Database *Non-Human Segmental Duplication Database Healthy control DNA samples from the Ontario Population Genomics Platform are available. The Biobanking and Databasing Facility provides DNA extraction from lymphoblasts, fibroblasts and other cell types, archiving of white cell pellets, preparation and immortalization of cell lines, and comprehensive databasing and tracking of samples and/or cell lines within the facility.

Proper citation: TCAG (RRID:SCR_001840) Copy   

•   Source: SciCrunch Registry

http://www.plantgdb.org/AtGDB/

Database providing a sequence-centered genome view for Arabidopsis thaliana, with a narrow focus on gene structure annotation. The current genome assembly displayed at AtGDB is version TAIR9. Annotated gene models are TAIR10. They have mapped the complete set of 176,915 publicly available Arabidopsis EST sequences onto the Arabidopsis genome using GeneSeqer, a spliced alignment program incorporating sequence similarity and splice site scoring. About 96% of the available ESTs could be properly aligned with a genomic locus, with the remaining ESTs deriving from organelle genomes and non-Arabidopsis sources or displaying insufficient sequence quality for alignment. The mapping provides verified sets of EST clusters for evaluation of EST clustering programs. Analysis of the spliced alignments suggests corrections to current gene structure annotation and provides examples of alternative and non-canonical pre-mRNA splicing.

Proper citation: Arabidopsis thaliana Genome Database (RRID:SCR_001901) Copy   

•   Source: SciCrunch Registry

http://gmod.org/wiki/Main_Page

A collection of open source software tools for creating and managing genome-scale biological databases. GMOD is made up databases, applications, and adaptor software that connects these components together. You can use it to create a small laboratory database of genome annotations, or a large web-accessible community database. At first GMOD just featured model organisms but now any organism with any kind of sequence associated with it is a good candidate as a subject for a GMOD database. There are GMOD databases with just protein sequence in them, with EST sequence only, those that are concerned primarily with gene expression, and even those dedicated to collections of RNA sequence. They have also heard of GMOD databases for oligonucleotides and plasmids.

Proper citation: Generic Model Organism Database Project (RRID:SCR_001731) Copy   

•   Source: SciCrunch Registry

http://www.aphidbase.com/aphidbase/

Aphid genome database. Facilitates community annotation of pea aphid genome by International Aphid Genomics Consortium (IAGC). It aims to store recently acquired genomic resources on aphids and compare them to other insect resources as functional annotation tools. AphidBase Information System designed to organize and distribute genomic data and annotations for large international community was constructed using open source software tools from Generic Model Organism Database (GMOD).

Proper citation: APHIDBASE (RRID:SCR_001765) Copy   

•   Source: SciCrunch Registry

http://www.aspergillus-genomes.org.uk/

A resource for viewing annotated genes arising from various Aspergillus sequencing and annotation projects, resulting from the merging of Central Aspergillus Data REpository (CADRE) and The Aspergillus Website, which took place in June 2008. The principal role of CADRE is to aid the Aspergillus research community by managing Aspergillus genome data and by providing visualization tools, ranging from relatively simple annotation displays to more complex data integration displays. In contrast, The Aspergillus Website provides a range of information to the medical community (i.e., clinicians, patients and scientists) regarding the genus Aspergillus and the diseases, such as Aspergillosis, that it can cause. CADRE has been implemented using the Ensembl v22 suite. This suite comprises: * a database schema, which has been devised for storing annotated eukaryotic genomes. The schema is implemented with the MySQL relational database management system. * several specialized programming modules for building interfaces (i.e., BioPerl and Ensembl API modules). * a series of programs (i.e., Perl CGI scripts using the API modules) for viewing genomic data within a web browser., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Aspergillus Genomes (RRID:SCR_001880) Copy   

•   Source: SciCrunch Registry

https://david.ncifcrf.gov/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025. Bioinformatics resource system including web server and web service for functional annotation and enrichment analyses of gene lists. Consists of comprehensive knowledgebase and set of functional analysis tools. Includes gene centered database integrating heterogeneous gene annotation resources to facilitate high throughput gene functional analysis.

Proper citation: DAVID (RRID:SCR_001881) Copy   

•   Source: SciCrunch Registry

http://mousecyc.jax.org/

A manually curated database of both known and predicted metabolic pathways for the laboratory mouse. It has been integrated with genetic and genomic data for the laboratory mouse available from the Mouse Genome Informatics database and with pathway data from other organisms, including human. The database records for 1,060 genes in Mouse Genome Informatics (MGI) are linked directly to 294 pathways with 1,790 compounds and 1,122 enzymatic reactions in MouseCyc. (Aug. 2013) BLAST and other tools are available. The initial focus for the development of MouseCyc is on metabolism and includes such cell level processes as biosynthesis, degradation, energy production, and detoxification. MouseCyc differs from existing pathway databases and software tools because of the extent to which the pathway information in MouseCyc is integrated with the wealth of biological knowledge for the laboratory mouse that is available from the Mouse Genome Informatics (MGI) database.

Proper citation: MouseCyc (RRID:SCR_001791) Copy   

•   Source: SciCrunch Registry

http://www.rrrc.us/

Supplies biomedical investigators with rat models, embryonic stem cells, related reagents, and protocols they require for their research. In addition to repository, cryostorage and distribution functions, RRRC can facilitate acquisition of rat strains from other international repositories as well as provide consultation and technical training to investigators using rat models.

Proper citation: Rat Resource and Research Center (RRID:SCR_002044) Copy   

•   Source: SciCrunch Registry

http://pfs.nus.edu.sg/(S(dyrcwejlfws33vxe23zlvrf3))/CopyRightNotice.aspx?ReturnURL=%2fQueryInterface_V5_2.aspx

Search engine integrating various bio-informatic resources and algorithims to produce a one-stop resource for biologists to identify potentially functional SNPs. It caters to different groups of scientists interested in SNPs including those working in the following areas: * Whole-genome association studies * Gene-based association studies * Designing experiments to address the functionality of specific SNPs * Determining potentially functionally significant SNPs that are in LD with non-pfSNPs of interest. Users may add published SNP functions.

Proper citation: pfSNP (RRID:SCR_002167) Copy   

•   Source: SciCrunch Registry

http://www.candidagenome.org/

Database of genetic and molecular biological information about Candida albicans. Contains information about genes and proteins, descriptions and classifications of their biological roles, molecular functions, and subcellular localizations, gene, protein, and chromosome sequence information, tools for analysis and comparison of sequences and links to literature information. Each CGD gene or open reading frame has an individual Locus Page. Genetic loci that are not tied to DNA sequence also have Locus Pages. Provides Gene Ontology, GO, to all its users. Three ontologies that comprise GO (Molecular Function, Cellular Component, and Biological Process) are used by multiple databases to annotate gene products, so that this common vocabulary can be used to compare gene products across species. Development of ontologies is ongoing in order to incorporate new information. Data submissions are welcome.

Proper citation: Candida Genome Database (RRID:SCR_002036) Copy   

•   Source: SciCrunch Registry

http://genome.jgi.doe.gov/

Portal providing access to all JGI genomic databases and analytical tools, sequencing projects and their status, search for and download assemblies and annotations of sequenced genomes, and interactively explore those genomes and compare them with other sequenced microbes, fungi, plants or metagenomes using specialized systems tailored to each particular class of organisms. The Department of Energy (DOE) Joint Genome Institute (JGI) is a national user facility with massive-scale DNA sequencing and analysis capabilities dedicated to advancing genomics for bioenergy and environmental applications. Beyond generating tens of trillions of DNA bases annually, the Institute develops and maintains data management systems and specialized analytical capabilities to manage and interpret complex genomic data sets, and to enable an expanding community of users around the world to analyze these data in different contexts over the web.

Proper citation: JGI Genome Portal (RRID:SCR_002383) Copy   

•   Source: SciCrunch Registry

http://rgp.dna.affrc.go.jp/E/index.html

Rice Genome Research Program (RGP) is an integral part of the Japanese Ministry of Agriculture, Forestry and Fisheries (MAFF) Genome Research Project. RGP now aims to completely sequence the entire rice genome and subsequently to pursue integrated goals in functional genomics, genome informatics and applied genomics. It is jointly coordinated by the National Institute of Agrobiological Sciences (NIAS), a government research institute under MAFF and the Society for Techno-innovation of Agriculture, Forestry and Fisheries (STAFF), a semi-private research organization managed and supported by MAFF and a consortium of some twenty Japanese companies. The research is funded with yearly grants from MAFF and additional funds from the Japan Racing Association (JRA). It is now the leading member of the International Rice Genome Sequencing Project (IRGSP), a consortium of ten countries sharing the sequencing of the 12 rice chromosomes. The IRGSP adopts the clone-by-clone shotgun sequencing strategy so that each sequenced clone can be associated with a specific position on the genetic map and adheres to the policy of immediate release of the sequence data to the public domain. In December 2004, the IRGSP completed the sequencing of the rice genome. The high-quality and map-based sequence of the entire genome is now available in public databases.

Proper citation: Rice Genome Research Project (RRID:SCR_002268) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/rat/public/index_main.html

Data set of pictures representing genetic linkage maps of the rat resulting from the integration of two F2 intercrosses (SHRSP x BN and FHH x ACI). Markers in common between the two crosses are connected by a line to define integration points. There are a total of 4,786 markers on these maps; 4375 WIBR/MIT CGR markers; 223 markers from the previously released Mit/Mgh rat maps and 188 markers from the National Institute of Arthritis and Musculoskeletal and Skin Diseases Arb rat maps. Pictures are drawn to a scale of 5cm (Kosombi) per inch. The changes in color of the backbone of the chromosome for each cross represents the space between any two framework loci. Markers in blue type are framework loci. Markers in green type are unique placement loci. Markers in black type are bouncy placement loci.

Proper citation: Genetic Maps of the Rat Genome (RRID:SCR_002266) Copy   

•   Source: SciCrunch Registry

http://beetlebase.org/

A centralized sequence database and community resource for Tribolium genetics, genomics and developmental biology containing genomic sequence scaffolds mapped to 10 linkage groups, genetic linkage maps, the official gene set, Reference Sequences from NCBI (RefSeq), predicted gene models, ESTs and whole-genome tiling array data representing several developmental stages. The current version of Beetlebase is built on the Tribolium castaneum 3.0 Assembly (Tcas 3.0) released by the Human Genome Sequencing Center at the Baylor College of Medicine. The database is constructed using the upgraded Generic Model Organism Database (GMOD) modules. The genomic data is stored in a PostgreSQL relational database using the Chado schema and visualized as tracks in GBrowse. The genetic map is visualized using the comparative genetic map viewer CMAP. To enhance search capabilities, the BLAST search tool has been integrated with the GMOD tools. Tribolium castaneum is a very sophisticated genetic model organism among higher eukaryotes. As the member of a primitive order of holometabolous insects, Coleoptera, Tribolium is in a key phylogenetic position to understand the genetic innovations that accompanied the evolution of higher forms with more complex development. Coleoptera is also the largest and most species diverse of all eukaryotic orders and Tribolium offers the only genetic model for the profusion of medically and economically important species therein. The genome sequences may be downloaded.

Proper citation: BeetleBase (RRID:SCR_001955) Copy   

•   Source: SciCrunch Registry

http://www.uib.no/en/cbu

An inter-department center that conducts bioinformatics research and expands the interface between bioinformatics and experimental biological and biomedical research. The unit is closely associated with the the Bioinformatics group at the Department of Informatics (II) and has tight links with the Sars Centre for Marine Molecular biology (SARS) and the Department of Molecular Biology (MBI). Six research groups are currently associated with CBU with projects that include sequence and structure analysis, molecular evolution, genome annotation and genomics data analysis. CBU also provides services and contributes to bioinformatics education primarily through training courses.

Proper citation: University of Bergen Computational Biology Unit (RRID:SCR_002970) Copy   

•   Source: SciCrunch Registry

http://blocks.fhcrc.org/blocks/codehop.html

This COnsensus-DEgenerate Hybrid Oligonucleotide Primer (CODEHOP) strategy has been implemented as a computer program that is accessible over the World-Wide Web and is directly linked from the BlockMaker multiple sequence alignment site for hybrid primer prediction beginning with a set of related protein sequences. This is a new primer design strategy for PCR amplification of unknown targets that are related to multiply-aligned protein sequences. Each primer consists of a short 3' degenerate core region and a longer 5' consensus clamp region. Only 3-4 highly conserved amino acid residues are necessary for design of the core, which is stabilized by the clamp during annealing to template molecules. During later rounds of amplification, the non-degenerate clamp permits stable annealing to product molecules. The researchers demonstrate the practical utility of this hybrid primer method by detection of diverse reverse transcriptase-like genes in a human genome, and by detection of C5 DNA methyltransferase homologs in various plant DNAs. In each case, amplified products were sufficiently pure to be cloned without gel fractionation. Sponsors: This work was supported in part by a grant from the M. J. Murdock Charitable Trust and by a grant from NIH. S. P. is a Howard Hughes Medical Institute Fellow of the Life Sciences Research Foundation., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 15,2026.

Proper citation: COnsensus-DEgenerate Hybride Oligonucleotide Primers (RRID:SCR_002875) Copy   

•   Source: SciCrunch Registry

http://genome.jgi.doe.gov/programs/fungi/index.jsf

Fungal genomics database and interactive analytical tools that integrates all fungal genomes for diverse fungi that are important for energy and environment, the focus of the JGI Fungal program. It integrates genomics data from the DOE JGI and its users and promotes user community participation in data submission, annotation and analysis. Over 100 newly sequenced and annotated fungal genomes from JGI and elsewhere are available to the public through MycoCosm, and new annotated genomes are being added to this resource upon completion of annotation. MycoCosm offers web-based genome analysis tools for fungal biologists to ''navigate'' through sequenced genomes and explore them in the context of ''genome-centric'' and ''comparative views''.

Proper citation: MycoCosm (RRID:SCR_005312) Copy   

•   Source: SciCrunch Registry

http://last.cbrc.jp/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software tool for aligning sequences, similar to BLAST 2 sequences that colour-codes the alignments by reliability. Another useful feature of LAST is that it can compare huge (vertebrate-genome-sized) datasets. Unfortunately, this only applies to the downloadable version of LAST, not the web service. The web service can just about handle bacterial genomes, but it will take a few minutes and the output will be large. LAST can: * Handle big sequence data, e.g: ** Compare two vertebrate genomes ** Align billions of DNA reads to a genome * Indicate the reliability of each aligned column. * Use sequence quality data properly. * Compare DNA to proteins, with frameshifts. * Compare PSSMs to sequences * Calculate the likelihood of chance similarities between random sequences. LAST cannot (yet): * Do spliced alignment., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: LAST (RRID:SCR_006119) Copy   

•   Source: SciCrunch Registry

https://www.facebase.org/

A web portal that provides access to data, tools and materials that will aid in craniofacial research. Included is access to genomic and imaging based data sets from a variety of species, including zebrafish, human and mouse.

Proper citation: FaceBase (RRID:SCR_005998) Copy   

•   Source: SciCrunch Registry

https://www.iscaconsortium.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on June 22, 2022. A rapidly growing group of clinical cytogenetics and molecular genetics laboratories committed to improving quality of patient care related to clinical genetic testing using new molecular cytogenetic technologies including array comparative genomic hybridization (aCGH) and quantitative SNP analysis by microarrays or bead chip technology. They improve clinical care by providing a large publicly available database and forum where clinicians and researchers can share knowledge to expedite the understanding of copy number variation (CNV) in an abnormal population. The ISCA database contains whole genome array data from a subset of the ISCA Consortium clinical diagnostic laboratories. Array analysis was carried out on individuals with phenotypes including intellectual disability, autism, and developmental delay. Efforts of the Consortium include: # Clinical Utility: The ISCA Consortium has made recommendations regarding the appropriate clinical indications for cytogenetic array testing (Miller et al. AJHG 2010, PMID: 20466091). Currently, discussions are focused on pediatric applications for children with unexplained developmental delay, intellectual disability, autism and other developmental disabilities. A separate committee has been developed to address appropriate cancer genetic applications (http://www.urmc.rochester.edu/ccmc/). # Evidence-based standards for cytogenomic array design: The Consortium will develop recommendations for standards for the design, resolution and content of cytogenomic arrays using an evidence-based process and an international panel of experts in clinical genetics, clinical laboratory genetics (cytogenetics and molecular genetics), genomics and bioinformatics. This design is intended to be platform and vendor-neutral (common denominator is genome sequence coordinates), and is a dynamic process with input from the broader genetics community and evidence-based review by the expert panel (which will evolve into a Standing Committee with international representation). # Public Database for clinical and research community: It is essential that publicly available databases be created and maintained for cytogenetic array data generated in clinical testing laboratories. The ISCA data will be held in dbGaP and dbVar at NCBI/NIH and curated by a committee of clinical genetics laboratory experts. The very high quality of copy number data (i.e., deletions and duplications) coming from clinical laboratories combined with expert curation will produce an invaluable resource to the clinical and research communities. # Standards for interpretation of cytogenetic array results: Using the ISCA Database, along with other genomic and genetics databases, the Consortium will develop recommendations for the interpretation and reporting of pathogenic vs. benign copy number changes as well as imbalances of unknown clinical significance.

Proper citation: ISCA Consortium (RRID:SCR_006168) Copy   

•   Source: SciCrunch Registry