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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

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   

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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   

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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   

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http://www.ensembl.org/

Collection of genome databases for vertebrates and other eukaryotic species with DNA and protein sequence search capabilities. Used to automatically annotate genome, integrate this annotation with other available biological data and make data publicly available via web. Ensembl tools include BLAST, BLAT, BioMart and the Variant Effect Predictor (VEP) for all supported species.

Proper citation: Ensembl (RRID:SCR_002344) Copy   

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http://biocyc.org/

A collection of Pathway/Genome Databases which describes the genome and metabolic pathways of a single organism. The BioCyc collection of Pathway/Genome Databases (PGDBs) provides an electronic reference source on the genomes and metabolic pathways of sequenced organisms. BioCyc PGDBs are generated by software that predicts the metabolic pathway complements of completely sequenced organisms from their genome sequences. They also include the results of a number of other computational inference procedures applied to these genomes, including predictions of which genes code for missing enzymes in metabolic pathways, and predicted operons. The BioCyc Web site provides a suite of software tools for database searching and visualization, for omics data analysis, and for comparative genomics and comparative pathway questions. The databases within the BioCyc collection are organized into tiers according to the amount of manual review and updating they have received. Tier 1 PGDBs have been created through intensive manual efforts, and receive continuous updating. Tier 2 PGDBs were computationally generated by the PathoLogic program, and have undergone moderate amounts of review and updating. Tier 3 PGDBs were computationally generated by the PathoLogic program, and have undergone no review and updating. There are 967 DBs in Tier 3. The downloadable version of BioCyc that includes the Pathway Tools software provides more speed and power than the BioCyc Web site.

Proper citation: BioCyc (RRID:SCR_002298) Copy   

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http://camera.calit2.net/

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 26, 2016; however, the URL provides links to associated projects and data. A suite of data query, download, upload, analysis and sharing tools serving the needs of the microbial ecology research community, and other scientists using metagenomics data.

Proper citation: Community Cyberinfrastructure for Advanced Marine Microbial Ecology Research and Analysis (RRID:SCR_002676) Copy   

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http://www.hgsc.bcm.tmc.edu/content/honey-bee-genome-project

The HGSC has sequenced the honey bee, Apis mellifera. The version 4.0 assembly was released in March 2006 and published in October 2006. The genome sequence is being upgraded with additional sequence coverage. The honey bee is important in the agricultural community as a producer of honey and as a facilitator of pollination. It is a model organism for studying the following human health issues: immunity, allergic reaction, antibiotic resistance, development, mental health, longevity and diseases of the X chromosome. In addition, biologists are interested in the honey bee's social organization and behavioral traits. This project was proposed to the HGSC by a group of dedicated insect biologists, headed by Gene Robinson. Following a workshop at the HGSC and a honey bee white paper, the HGSC began the project in 2002. A 6-fold coverage WGS, BAC sequence from pooled arrays, and an initial genome assembly (Amel_v1.0) were released beginning in 2003. This has been a challenging project with difficulty in recovering AT-rich regions. The WGS data had lower coverage in AT-rich regions and BAC data from clones showed evidence of internal deletions. Additional reads from AT enriched DNA addressed these underrepresented regions. The current assembly Amel_4.0 was produced with Atlas and includes 2.7 million reads (1.8 Gb) or 7.5x coverage of the (clonable) genome. About 97% of STSs, 98% of ESTs, and 96% of cDNAs are represented in the 231 Mb assembly. About 2,500 reads were also produced from a strain of Africanized honey bee and SNPs were extracted. These were released in dbSNP and the NCBI Trace Archive. Analysis of the genome by a consortium of 20 labs has been completed. This produced a gene list derived from five different methods melded through the GLEAN software. Publications include a main paper in Nature and up to forty companion papers in Genome Research and Insect Molecular Biology. Sponsors: Sequencing of the honey bee is jointly funded by National Human Genome Research Institute (NHGRI) and the Department of Agriculture (USDA). Multiple drones from the same queen (strain DH4) were obtained from Danny Weaver of B. Weaver Apiaries. All libraries were made from DNA isolated from these drones. The honey bee BAC library (CHORI-224) was prepared by Pieter de Jong and Katzutoyo Osoegawa at the Children's Hospital Oakland Research Institute.

Proper citation: Honey Bee Genome Project (RRID:SCR_002890) Copy   

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http://rana.lbl.gov/drosophila

A single source for sequences, assemblies, annotations and analyses of the genomes of members of the fruitfly genus Drosophlia. It is meant as resource for Drosophilists and other researchers interested in comparative analysis of these species and their genomes. There are pages for each species, as well as pages for different types of multi-species resources (e.g. alignments). If you have a public resource that will help this project, please consider making it available through this page by emailing multiple_at_fruitfly.org.

Proper citation: Assembly/Alignment/Annotation of 12 Related Drosophila Species (RRID:SCR_002921) Copy   

•   Source: SciCrunch Registry

http://www.gramene.org

Curated, open-source, integrated data resource for comparative functional genomics in crops and model plant species to facilitate the study of cross-species comparisons using information generated from projects supported by public funds. It currently hosts annotated whole genomes in over two dozen plant species and partial assemblies for almost a dozen wild rice species in the Ensembl browser, genetic and physical maps with genes, ESTs and QTLs locations, genetic diversity data sets, structure-function analysis of proteins, plant pathways databases (BioCyc and Plant Reactome platforms), and descriptions of phenotypic traits and mutations. The web-based displays for phenotypes include the Genes and Quantitative Trait Loci (QTL) modules. Sequence based relationships are displayed in the Genomes module using the genome browser adapted from Ensembl, in the Maps module using the comparative map viewer (CMap) from GMOD, and in the Proteins module displays. BLAST is used to search for similar sequences. Literature supporting all the above data is organized in the Literature database. In addition, Gramene now hosts a variety of web services including a Distributed Annotation Server (DAS), BLAST and a public MySQL database. Twice a year, Gramene releases a major build of the database and makes interim releases to correct errors or to make important updates to software and/or data. Additionally you can access Gramene through an FTP site.

Proper citation: Gramene (RRID:SCR_002829) Copy   

•   Source: SciCrunch Registry

http://www.hgsc.bcm.tmc.edu/content/red-flour-beetle-genome-project

This portal provides information about the Tribolium castabeum Genome Project. The Tribolium castaneum genome sequence and its analysis has been published in Nature, two companion journal issues (IBMB and DGE) and numerous other publications listed below. The red flour beetle, Tribolium castaneum, a common pest that is also a genetic model for the Coleoptera. The genome has been sequenced to 7-fold coverage using a whole genome shotgun approach and assembled using the HGSC's assembly engine, Atlas, with methods employed for the Drosophila pseudoobscura genome assembly. Approximately 90% of the genome sequence has been mapped to chromosomes in collaboration with Dick Beeman (USDA ARS) and Sue Brown (Kansas State University). Access to the Data :- Genome Assembly: The long term home of the Tribolium genome is Beetlebase. Tcas 3.0 is now available in GenBank and on our FTP site. Note there are no restrictions of any kind on the Tribolium data as it has been published. Version 2 of the assembly, Tcas_2.0 is available for download using the FTP Data link in the sidebar. The assembly is described in detail in the README in that directory. T.cas_1.0 was a preliminary genome assembly that did not include large insert paired end information and has been moved to a previous assemblies folder. A genboree browser of the Tcas2.0 sequence is available here: There are also links to the genboree browser from the blast results (at the bottom of each reported HSP) if you use the blast server on this page. The original linear scaffold file, Tcas2.0/linearScaffolds/Tcas20050914-genome, posted on the ftp site did not include singleton contigs from the assembly and thus did not fully reflect the tribolium genome sequence, missing ~4.4Mb of sequence in 1860 contigs and reptigs or approximately 2.5% of the assembled sequence. A corrected Tcas20051011-genome file containing these missing sequences is now available on the ftp site. The blast databases have also been updated to reflect this change. All other data is correct, and not affected by this change. :- BLAST Searches: The BLAST link is located in the sidebar. :* Linearized chromosome and unplaced scaffold sequences :* Assembled contigs :* Bin0 unassembled reads and Repeat reads Traces are available from the NCBI Trace Archive by using the link in the sidebar, or by using NCBI MegaBLAST with a same species or cross species query. Sponsors: Funding for this project has been provided by the National Human Genome Research Institute (NHGRI U54 HG003273), which is part of the National Institutes of Health (NIH), and the U.S. Department of Agriculture's Agricultural Research Service (USDA ARS Agreement No. 58-5430-3-338).

Proper citation: Tribolium castaneum Genome Project (RRID:SCR_002848) Copy   

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http://hapmap.ncbi.nlm.nih.gov/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. A multi-country collaboration among scientists and funding agencies to develop a public resource where genetic similarities and differences in human beings are identified and catalogued. Using this information, researchers will be able to find genes that affect health, disease, and individual responses to medications and environmental factors. All of the information generated by the Project will be released into the public domain. Their goal is to compare the genetic sequences of different individuals to identify chromosomal regions where genetic variants are shared. Public and private organizations in six countries are participating in the International HapMap Project. Data generated by the Project can be downloaded with minimal constraints. HapMap project related data, software, and documentation include: bulk data on genotypes, frequencies, LD data, phasing data, allocated SNPs, recombination rates and hotspots, SNP assays, Perlegen amplicons, raw data, inferred genotypes, and mitochondrial and chrY haplogroups; Generic Genome Browser software; protocols and information on assay design, genotyping and other protocols used in the project; and documentation of samples/individuals and the XML format used in the project.

Proper citation: International HapMap Project (RRID:SCR_002846) Copy   

•   Source: SciCrunch Registry

http://hembase.niddk.nih.gov/

Database designed for web-based examination of the human erythroid transcriptome. The database is organized to provide a cytogenetic band position, a unique name as well as a concise annotation for each entry. Search queries may be performed by name, keyword or cytogenetic location. Search results are linked to primary sequence data and three major human genome browsers for access to information considered current at the time of each search. Hembase provides interested scientists and clinical hematologists with a genome-based approach toward the study of erythroid biology. Red blood cells in the circulation arise from hematopoietic stem cells that proliferate as erythroid progenitors and differentiate into erythroid precursor cells in response to the hormone erythropoietin. Messenger RNA was isolated from those cells and used to generate gene libraries. Sequencing several thousand expressed sequence tags (EST) from those libraries was then performed. Those EST and sequences encoding several hundred additional genes with known expression in erythroid cells are compiled here as a database of human erythroid gene activity. The database is organized and linked according to the location of these sequences within the human genome., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 15,2026.

Proper citation: HemBase (RRID:SCR_002880) Copy   

•   Source: SciCrunch Registry

http://www.atgc-montpellier.fr/

A bioinformatics platform that is a joint project of several South of France laboratories with available services based on their expertise, issued from their research activities which involve phylogenetics, population genetics, molecular evolution, genome dynamics, comparative and functional genomics, and transcriptome analysis. Most of the software and databases on ATGC are (co)authored by researchers from South of France teams. Some are widely used and highly cited. South of France laboratories: * CRBM (transcriptomes and stem cells). * IBC (computational biology). * MiVEGEC (evolution and phylogeny). * LGDP (plant genomics). * LIRMM (computer science). * South Green (plant genomics).

Proper citation: ATGC: Montpellier bioinformatics platform (RRID:SCR_002917) Copy   

•   Source: SciCrunch Registry

http://www.brenda-enzymes.org/

Database for functional enzyme and ligand-related information maintained as part of the German ELIXIR Node. Provides advanced query systems, evaluation tools, and various visualization options for the detailed assessment of enzyme properties. Enzyme data in BRENDA are classified according to the Enzyme Commission (EC) nomenclature of IUBMB.

Proper citation: BRENDA (RRID:SCR_002997) 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

https://gitlab.sib.swiss/EPD/chipseq

Set of software modules for performing common ChIP-seq data analysis tasks across the whole genome, including positional correlation analysis, peak detection, and genome partitioning into signal-rich and signal-poor regions. The tools are designed to be simple, fast and highly modular. Each program carries out a well-defined data processing procedure that can potentially fit into a pipeline framework. ChIP-Seq is also freely available on a Web interface.

Proper citation: ChIP-seq (RRID:SCR_001237) Copy   

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http://blast.ncbi.nlm.nih.gov/Blast.cgi?PROGRAM=blastx&BLAST_PROGRAMS=blastx&PAGE_TYPE=BlastSearch&SHOW_DEFAULTS=on&LINK_LOC=blasthome

Web application to search protein databases using a translated nucleotide query. Translated BLAST services are useful when trying to find homologous proteins to a nucleotide coding region. Blastx compares translational products of the nucleotide query sequence to a protein database. Because blastx translates the query sequence in all six reading frames and provides combined significance statistics for hits to different frames, it is particularly useful when the reading frame of the query sequence is unknown or it contains errors that may lead to frame shifts or other coding errors. Thus blastx is often the first analysis performed with a newly determined nucleotide sequence and is used extensively in analyzing EST sequences. This search is more sensitive than nucleotide blast since the comparison is performed at the protein level.

Proper citation: BLASTX (RRID:SCR_001653) Copy   

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https://rgd.mcw.edu/rgdweb/portal/home.jsp?p=4

An integrated resource for information on genes, QTLs and strains associated with diabetes. The portal provides easy acces to data related to both Type 1 and Type 2 Diabetes and Diabetes-related Obesity and Hypertension, as well as information on Diabetic Complications. View the results for all the included diabetes-related disease states or choose a disease category to get a pull-down list of diseases. A single click on a disease will provide a list of related genes, QTLs, and strains as well as a genome wide view of these via the GViewer tool. A link from GViewer to GBrowse shows the genes and QTLs within their genomic context. Additional pages for Phenotypes, Pathways and Biological Processes provide one-click access to data related to diabetes. Tools, Related Links and Rat Strain Models pages link to additional resources of interest to diabetes researchers.

Proper citation: Diabetes Disease Portal (RRID:SCR_001660) Copy   

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http://alfred.med.yale.edu

A public curated compilation of allele frequency data on anthropologically defined human population samples linked to the molecular genetics-human genome databases. Only data on well defined population samples that are large enough to yield reasonably accurate frequencies and for polymorphisms sufficiently defined to be replicable can be included in ALFRED. Researchers wishing to have their data entered into ALFRED should contact them. Initially, ALFRED contained primarily data generated in the laboratories of K.K. and J.R. Kidd in the Department of Genetics at Yale, including extensive unpublished data. Data from the published literature are being entered into ALFRED in a systematic way, with a focus on polymorphisms studied in many different populations. ALFRED is distinct from such databases as dbSNP, which catalogs sequence variation. ALFRED's focus is on allele frequencies in diverse anthropologically defined populations. It is not a compendium of human DNA polymorphisms but of frequencies of selected polymorphisms with an emphasis on those that have been studied in multiple populations. All of the data in ALFRED are considered to be in the public domain and available for use in research and teaching. ALFRED provides easy searching options including versatile "Keyword search" and also has numerous summary tables providing quick overviews of contents by chromosome, population, average heterozygosity, Fst and others, all available under various tabs from the ALFRED homepage.

Proper citation: ALFRED (RRID:SCR_001730) Copy   

•   Source: SciCrunch Registry