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http://www.eucomm.org

Generate, archive, and distribute world-wide up to 12.000 conditional mutations across the mouse genome in mouse embryonic stem (ES) cells and Establish a limited number of mouse mutants from this resource. EUCOMM contributes the largest fraction of conditionally trapped and targeted genes in mouse C57BL/6N embryonic stem (ES) cells to the IKMC. EUCOMM vectors, mutant ES cells and mutant mice are distributed worldwide, enabling functional genomics research in a standardized and cost-effective manner by a much wider biomedical research community than has been possible previously. EUCOMM mutant ES cells and vectors can be obtained from the European Mouse Mutant Cell Repository (EuMMCR). EUCOMM mutant mice are archived and distributed by the European Mouse Mutant Archive (EMMA). Mutagenesis Strategies * Conditional gene trapping - random approach for expressed genes * Conditional targeted trapping - directed approach, used for expressed genes * Conditional gene targeting - directed approach, used for non-expressed genes

Proper citation: European Conditional Mouse Mutagenesis Program (RRID:SCR_003104) Copy   

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http://jaspar.genereg.net

Open source database of curated, non-redundant set of profiles derived from published collections of experimentally defined transcription factor binding sites for multicellular eukaryotes. Consists of open data access, non-redundancy and quality. JASPAR CORE is smaller set that is non-redundant and curated. Collection of transcription factor DNA-binding preferences, modeled as matrices. These can be converted into Position Weight Matrices (PWMs or PSSMs), used for scanning genomic sequences. Web interface for browsing, searching and subset selection, online sequence analysis utility and suite of programming tools for genome-wide and comparative genomic analysis of regulatory regions. New functions include clustering of matrix models by similarity, generation of random matrices by sampling from selected sets of existing models and a language-independent Web Service applications programming interface for matrix retrieval.

Proper citation: JASPAR (RRID:SCR_003030) Copy   

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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   

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http://www.coriell.org/

Non-profit research center dedicated to the study of the human genome. Expert staff and pioneering programs in the fields of personalized medicine, cell biology, cytogenetics, genotyping, and biobanking drive our mission. The emerging field of personalized medicine draws upon a person's genomic information to tailor treatments and prescription drug dosing to optimize health outcomes. The Coriell Personalized Medicine Collaborative (CPMC) research study is seeking to understand the usefulness of genetic risk and pharmacogenomics in clinical decision-making and healthcare management. Coriell has a distinguished history in cell biology. We are building upon this expertise by playing an important role in induced pluripotent stem (iPS) cell research. These powerful cells, which can be made from skin cells or blood, are revolutionizing the way human disease is studied and how drugs are developed. The decline of neurons afflicted with Alzheimer's disease or pancreatic cells fighting diabetes can be studied in a Petri dish. By proving efficacy within the diseased environment prior to clinical trial, drugs can move through the pipeline quicker to reach patients sooner. In addition to pioneering cutting-edge research initiatives, Coriell offers custom research services including cell culture, cytogenetic analyses, and molecular biology to the scientific community. Furthermore, Coriell's Genotyping and Microarray Center is one of the nation's largest centers, with high-throughput DNA analysis systems from Illumina and Affymetrix. The Center is CLIA-certified in 48 states.

Proper citation: Coriell Institute for Medical Research (RRID:SCR_003043) Copy   

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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   

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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   

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http://hugenavigator.net/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 5, 2023. Knowledge base of genetic associations and human genome epidemiology including information on population prevalence of genetic variants, gene-disease associations, gene-gene and gene- environment interactions, and evaluation of genetic tests. This tool explores HuGENet, the Human Genome Epidemiology Network, which is a global collaboration of individuals and organizations committed to the assessment of the impact of human genome variation on population health and how genetic information can be used to improve health and prevent disease. What does HuGE Navigator offer? *HuGEpedia - an encyclopedia of human genetic variation in health and disease, includes, Phenopedia and Genopedia. Phenopedia allows you to look up gene-disease association summaries by disease, and Genopedia allows you to look up gene-disease association summaries by gene. In general, HuGEpedia is a searchable database that summarizes published articles about human disease and genetic variation, including primary studies, reviews, and meta-analyses. It provides links to Pubmed abstracts, researcher contact info, trends, and more. *HuGEtools - searching and mining the literature in human genome epidemiology, includes, HuGE Literature Finder, HuGE Investigator Browser, Gene Prospector, HuGE Watch, Variant Name Mapper, and HuGE Risk Translator. *HuGE Literature Finder finds published articles in human genome epidemiology since 2001. The search query can include genes, disease, outcome, environmental factors, author, etc. Results can be filtered by these categories. It is also possible to see all articles in the database for a particular topic, such as genotype prevalence, pharmacogenomics, or clinical trial. *HuGE Investigator Browser finds investigators in a particular field of human genome epidemiology. This info is obtained using a behind-the-scenes tool that automatically parses PubMed affiliation data. *Gene Prospector is a gateway for evaluating genes in relation to disease and risk factors. This tool allows you to enter a disease or risk factor and then supplies you with a table of genes associated w/your query that are ranked based on strength of evidence from the literature. This evidence is culled from the HuGE Literature Finder and NCBI Entrez Gene - And you're given the scoring formula. The Gene Prospector results table provides access to the Genopedia entry for each gene in the list, general info including links to other resources, SNP info, and associated literature from HuGE, PubMed, GWAS, and more. It is a great place to locate a lot of info about your disease/gene of interest very quickly. *HuGE Watch tracks the evolution of published literature, HuGE investigators, genes studied, or diseases studied in human genome epidemiology. For example, if you search Trend/Pattern for Diseases Studied you'll initially get a graph and chart of the number of diseases studied per year since 1997. You can refine these results by limiting the temporal trend to a category or study type such as Gene-gene Interaction or HuGE Review. *Variant Name Mapper maps common names and rs numbers of genetic variants using information from SNP500Cancer, SNPedia, pharmGKB, ALFRED, AlzGene, PDGene, SZgene, HuGE Navigator, LSDBs, and user submissions. *HuGE Risk Translator calculates the predictive value of genetic markers for disease risk. To do so, users must enter the frequency of risk variant, the population disease risk, and the odds ratio between the gene and disease. This information is necessary in order to yield a useful predictive result. *HuGEmix - a series of HuGE related informatics utilities and projects, includes, GAPscreener, HuGE Track, Open Source. GAPscreener is a screening tool for published literature on human genetic associations; HuGE Track is a custom track built for HuGE data in the UCSC Genome Browser; and Open Source is infrastructure for managing knowledge and information from PubMed.

Proper citation: HuGE Navigator - Human Genome Epidemiology Navigator (RRID:SCR_003172) Copy   

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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   

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http://code.google.com/p/popoolation/

A collection of tools to facilitate population genetic studies of next generation sequencing data from pooled individuals. It builds upon open source tools (bwa, samtools) and uses standard file formats (gtf, sam, pileup) to ensure a wide compatibility. PoPoolation allows to calculate Tajima's Pi, Watterson's Theta and Tajima's D for reference sequences using a sliding window approach. Alternatively these population genetic estimators may be calculated for a set of genes (provided as gtf). One of the main challenges in population genomics is to identify regions of intererest on a genome wide scale. PoPoolation will greatly aid this task by allowing a fast and user friendly analysis of NGS data from DNA pools.

Proper citation: PoPoolation (RRID:SCR_003495) Copy   

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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   

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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   

•   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://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   

•   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://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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.omicia.com/products/opal-research

Software which integrates a comprehensive, automated genome annotation engine with the VAAST and Phevor disease gene prioritization tools to rank gene variants on the severity of their impact on protein function and likelihood to cause disease. Each variant in a gene is analyzed for its impact on protein function, conservation and frequency. Each gene is ranked rather than filtered in order to ensure critical targets are not prematurely removed.

Proper citation: Opal Research (RRID:SCR_000405) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/cancer/cga/mutect

Software for the reliable and accurate identification of somatic point mutations in next generation sequencing data of cancer genomes.

Proper citation: MuTect (RRID:SCR_000559) Copy   

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http://sourceforge.net/projects/reprever/?source=directory

Software that identifies (a) the insertion breakpoints where the extra duplicons inserted into the donor genome and (b) the actual sequence of the duplicon for any genomic regions that are increased in copy number.

Proper citation: Reprever (RRID:SCR_000463) Copy   

•   Source: SciCrunch Registry