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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://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://www.bioperl.org

BioPerl is a community effort to produce Perl code which is useful in biology. This toolkit of perl modules is useful in building bioinformatics solutions in Perl. It is built in an object-oriented manner so that many modules depend on each other to achieve a task. The collection of modules in the bioperl-live repository consist of the core of the functionality of bioperl. Additionally auxiliary modules for creating graphical interfaces (bioperl-gui), persistent storage in RDMBS (bioperl-db), running and parsing the results from hundreds of bioinformatics applications (Run package), software to automate bioinformatic analyses (bioperl-pipeline) are all available as Git modules in our repository. The BioPerl toolkit provides a library of hundreds of routines for processing sequence, annotation, alignment, and sequence analysis reports. It often serves as a bridge between different computational biology applications assisting the user to construct analysis pipelines. This chapter illustrates how BioPerl facilitates tasks such as writing scripts summarizing information from BLAST reports or extracting key annotation details from a GenBank sequence record. BioPerl includes modules written by Sohel Merchant of the GO Consortium for parsing and manipulating OBO ontologies. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: BioPerl (RRID:SCR_002989) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/gsea/

Software package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.

Proper citation: Gene Set Enrichment Analysis (RRID:SCR_003199) Copy   

•   Source: SciCrunch Registry

http://www.xenbase.org/

Data collection for Xenopus laevis and Xenopus tropicalis biology and genomics.

Proper citation: Xenbase (RRID:SCR_003280) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/genomation/

Software R package for simplfiying common tasks in genomic feature analysis. Toolkit to summarize, annotate and visualize genomic intervals. Provides functions for reading BED and GFF files as GRanges objects, summarizing genomic features over predefined windows so users can make average enrichment of features over defined regions or produce heatmaps. Can annotate given regions with other genomic features such as exons,introns and promoters.

Proper citation: genomation (RRID:SCR_003435) Copy   

•   Source: SciCrunch Registry

http://rulai.cshl.edu/SCPD/

A promoter database of Saccharomyces cerevisiae. Users can explore the promoter regions of ~6000 genes and ORFs in yeast genome, annotate putative regulatory sites of all genes and ORFs, locate intergenic regions, and retrieve sequence of the promoter region. In regards to regulatory elements and transcription factors, users can provide information on transcriptionally related genes, browse matrix and consensus sequences, view the correlation between elements, observe binding affinity and expression, and look at genomewise distribution. SCPD also provides some simple but useful tools for promoter sequence analysis. Gene, consensus and matrix records may be submitted.

Proper citation: SCPD - Saccharomyces cerevisiae promoter database (RRID:SCR_004412) Copy   

•   Source: SciCrunch Registry

http://sequenceontology.org/

A collaborative ontology for the definition of sequence features used in biological sequence annotation. SO was initially developed by the Gene Ontology Consortium. Contributors to SO include the GMOD community, model organism database groups such as WormBase, FlyBase, Mouse Genome Informatics group, and institutes such as the Sanger Institute and the EBI. Input to SO is welcomed from the sequence annotation community. The OBO revision is available here: http://sourceforge.net/p/song/svn/HEAD/tree/ SO includes different kinds of features which can be located on the sequence. Biological features are those which are defined by their disposition to be involved in a biological process. Biomaterial features are those which are intended for use in an experiment such as aptamer and PCR_product. There are also experimental features which are the result of an experiment. SO also provides a rich set of attributes to describe these features such as polycistronic and maternally imprinted. The Sequence Ontologies use the OBO flat file format specification version 1.2, developed by the Gene Ontology Consortium. The ontology is also available in OWL from Open Biomedical Ontologies. This is updated nightly and may be slightly out of sync with the current obo file. An OWL version of the ontology is also available. The resolvable URI for the current version of SO is http://purl.obolibrary.org/obo/so.owl.

Proper citation: SO (RRID:SCR_004374) Copy   

•   Source: SciCrunch Registry

http://bix.ucsd.edu/projects/singlecell/

Software package for short read data from single cells that improves assembly through use of progressively increasing coverage cutoff. Used for single cell Illumina sequences, allows variable coverage datasets to be utilized with assembly of E. coli and S. aureus single cell reads. Assembles single cell genome of uncultivated SAR324 clade of Deltaproteobacteria.

Proper citation: Velvet-SC (RRID:SCR_004377) Copy   

•   Source: SciCrunch Registry

http://www.genedb.org/Homepage/Lmajor

Database of the most recent sequence updates and annotations for the L. major genome. New annotations are constantly being added to keep up with published manuscripts and feedback from the Trypanosomatid research community. You may search by Protein Length, Molecular Mass, Gene Type, Date, Location, Protein Targeting, Transmembrane Helices, Product, GO, EC, Pfam ID, Curation and Comments, and Dbxrefs. BLAST and other tools are available. Leishmania species cause a spectrum of human diseases in tropical and subtropical regions of the world. We have sequenced the 36 chromosomes of the 32.8-megabase haploid genome of Leishmania major (Friedlin strain) and predict 911 RNA genes, 39 pseudogenes, and 8272 protein-coding genes, of which 36% can be ascribed a putative function. These include genes involved in host-pathogen interactions, such as proteolytic enzymes, and extensive machinery for synthesis of complex surface glycoconjugates. The Pathogen Genomics group at the Wellcome Trust Sanger Institute played a major role in sequencing the genome of Leishmania major (see Ivens et al.) Details of the centres involved and which chromosomes they sequenced, are given. The sequence data were obtained by adopting several parallel approaches, including complete cosmid sequencing, whole chromosome shotguns and/or BAC sequencing/skimming. The Leishmania parasite is an intracellular pathogen of the immune system targeting macrophages and dendritic cells. The disease Leishmaniasis affects the populations of 88 counties worldwide with symptoms ranging from disfiguring cutaneous and muco-cutaneous lesions that can cause widespread destruction of mucous membranes to visceral disease affecting the haemopoetic organs. In collaboration with GeneDB, the EuPathDB genomic sequence data and annotations are regularly deposited on TriTrypDB where they can be integrated with other datasets and queried using customized queries.

Proper citation: GeneDB Lmajor (RRID:SCR_004613) Copy   

•   Source: SciCrunch Registry

http://blast.ncbi.nlm.nih.gov/Blast.cgi

Web search tool to find regions of similarity between biological sequences. Program compares nucleotide or protein sequences to sequence databases and calculates statistical significance. Used for identifying homologous sequences.

Proper citation: NCBI BLAST (RRID:SCR_004870) Copy   

•   Source: SciCrunch Registry

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

Nucleotide database as collection of sequences from several sources, including GenBank, RefSeq, TPA and PDB. Genome, gene and transcript sequence data provide the foundation for biomedical research and discovery.

Proper citation: Nucleotide database (RRID:SCR_004630) Copy   

•   Source: SciCrunch Registry

http://www.pantherdb.org/

System that classifies genes by their functions, using published scientific experimental evidence and evolutionary relationships to predict function even in absence of direct experimental evidence. Orthologs view is curated orthology relationships between genes for human, mouse, rat, fish, worm, and fly., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PANTHER (RRID:SCR_004869) Copy   

•   Source: SciCrunch Registry