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http://www.cidr.jhmi.edu/

Next generation sequencing and genotyping services provided to investigators working to discover genes that contribute to disease. On-site statistical geneticists provide insight into analysis issues as they relate to study design, data production and quality control. In addition, CIDR has a consulting agreement with the University of Washington Genetics Coordinating Center (GCC) to provide statistical and analytical support, most predominantly in the areas of GWAS data cleaning and methods development. Completed studies encompass over 175 phenotypes across 530 projects and 620,000 samples. The impact is evidenced by over 380 peer-reviewed papers published in 100 journals. Three pathways exist to access the CIDR genotyping facility: * NIH CIDR Program: The CIDR contract is funded by 14 NIH Institutes and provides genotyping and statistical genetic services to investigators approved for access through competitive peer review. An application is required for projects supported by the NIH CIDR Program. * The HTS Facility: The High Throughput Sequencing Facility, part of the Johns Hopkins Genetic Resources Core Facility, provides next generation sequencing services to internal JHU investigators and external scientists on a fee-for-service basis. * The JHU SNP Center: The SNP Center, part of the Johns Hopkins Genetic Resources Core Facility, provides genotyping to internal JHU investigators and external scientists on a fee-for-service basis. Data computation service is included to cover the statistical genetics services provided for investigators seeking to identify genes that contribute to human disease. Human Genotyping Services include SNP Genome Wide Association Studies, SNP Linkage Scans, Custom SNP Studies, Cancer Panel, MHC Panels, and Methylation Profiling. Mouse Genotyping Services include SNP Scans and Custom SNP Studies.

Proper citation: Center for Inherited Disease Research (RRID:SCR_007339) Copy   

•   Source: SciCrunch Registry

https://www.mc.vanderbilt.edu/victr/dcc/projects/acc/index.php/Main_Page

A national consortium formed to develop, disseminate, and apply approaches to research that combine DNA biorepositories with electronic medical record (EMR) systems for large-scale, high-throughput genetic research. The consortium is composed of seven member sites exploring the ability and feasibility of using EMR systems to investigate gene-disease relationships. Themes of bioinformatics, genomic medicine, privacy and community engagement are of particular relevance to eMERGE. The consortium uses data from the EMR clinical systems that represent actual health care events and focuses on ethical issues such as privacy, confidentiality, and interactions with the broader community.

Proper citation: eMERGE Network: electronic Medical Records and Genomics (RRID:SCR_007428) Copy   

•   Source: SciCrunch Registry

http://plantgrn.noble.org/LegumeIP/

LegumeIP is an integrative database and bioinformatics platform for comparative genomics and transcriptomics to facilitate the study of gene function and genome evolution in legumes, and ultimately to generate molecular based breeding tools to improve quality of crop legumes. LegumeIP currently hosts large-scale genomics and transcriptomics data, including: * Genomic sequences of three model legumes, i.e. Medicago truncatula, Glycine max (soybean) and Lotus japonicus, including two reference plant species, Arabidopsis thaliana and Poplar trichocarpa, with the annotation based on UniProt TrEMBL, InterProScan, Gene Ontology and KEGG databases. LegumeIP covers a total 222,217 protein-coding gene sequences. * Large-scale gene expression data compiled from 104 array hybridizations from L. japonicas, 156 array hybridizations from M. truncatula gene atlas database, and 14 RNA-Seq-based gene expression profiles from G. max on different tissues including four common tissues: Nodule, Flower, Root and Leaf. * Systematic synteny analysis among M. truncatula, G. max, L. japonicus and A. thaliana. * Reconstruction of gene family and gene family-wide phylogenetic analysis across the five hosted species. LegumeIP features comprehensive search and visualization tools to enable the flexible query on gene annotation, gene family, synteny, relative abundance of gene expression.

Proper citation: LegumeIP (RRID:SCR_008906) Copy   

•   Source: SciCrunch Registry

http://hymenopteragenome.org/beebase/

Gene sequences and genomes of Bombus terrestris, Bombus impatiens, Apis mellifera and three of its pathogens, that are discoverable and analyzed via genome browsers, blast search, and apollo annotation tool. The genomes of two additional species, Apis dorsata and A. florea are currently under analysis and will soon be incorporated.BeeBase is an archive and will not be updated. The most up-to-date bee genome data is now available through the navigation bar on the HGD Home page.

Proper citation: BeeBase (RRID:SCR_008966) Copy   

•   Source: SciCrunch Registry

http://rgd.mcw.edu/rgdCuration/?module=portal&func=show&name=renal

An integrated resource for information on genes, QTLs and strains associated with a variety of kidney and renal system conditions such as Renal Hypertension, Polycystic Kidney Disease and Renal Insufficiency, as well as Kidney Neoplasms.

Proper citation: Renal Disease Portal (RRID:SCR_009030) Copy   

•   Source: SciCrunch Registry

http://enhancer.lbl.gov/

Resource for experimentally validated human and mouse noncoding fragments with gene enhancer activity as assessed in transgenic mice. Most of these noncoding elements were selected for testing based on their extreme conservation in other vertebrates or epigenomic evidence (ChIP-Seq) of putative enhancer marks. Central public database of experimentally validated human and mouse noncoding fragments with gene enhancer activity as assessed in transgenic mice. Users can retrieve elements near single genes of interest, search for enhancers that target reporter gene expression to particular tissue, or download entire collections of enhancers with defined tissue specificity or conservation depth.

Proper citation: VISTA Enhancer Browser (RRID:SCR_007973) Copy   

•   Source: SciCrunch Registry

http://vega.sanger.ac.uk/

Central repository for high quality frequently updated manual annotation of vertebrate finished genome sequence. Human, mouse and zebrafish are in the process of being completely annotated, whereas for other species the annotation is only of specific genomic regions of particular biological interest. The majority of the annotation is from the HAVANA group at the Welcome Trust Sanger Institute. Users can BLAST, search for specific text, export, and download data. Genomes and details of the projects for each species are available through the homepages for human mouse and zebrafish. The website is built upon code from the EnsEMBL (http://www.ensembl.org) project. Some Ensembl features are not available in Vega. From the users point of view perhaps the most significant of these is MartView. However due to their inclusion in Ensembl, Vega human and mouse data can be queried using Ensembl MartView. Vega contains annotation of the human MHC region in eight haplotypes, and the LRC region in three haplotypes. Vega also contains annotation on the Insulin Dependent Diabetes (IDD) regions on non-reference assemblies for mouse.

Proper citation: VEGA (RRID:SCR_007907) Copy   

•   Source: SciCrunch Registry

http://rfam.xfam.org/

The Rfam database is a collection of RNA families, each represented by multiple sequence alignments, consensus secondary structures and covariance models (CMs). The families in Rfam break down into three broad functional classes: Non-coding RNA genes, structured cis-regulatory elements and self-splicing RNAs. Typically these functional RNAs often have a conserved secondary structure which may be better preserved than the RNA sequence. The CMs used to describe each family are a slightly more complicated relative of the profile hidden Markov models (HMMs) used by Pfam. CMs can simultaneously model RNA sequence and the structure in an elegant and accurate fashion. Rfam is also available via FTP. You can find data in Rfam in various ways... * Analyze your RNA sequence for Rfam matches * View Rfam family annotation and alignments * View Rfam clan details * Query Rfam by keywords * Fetch families or sequences by NCBI taxonomy * Enter any type of accession or ID to jump to the page for a Rfam family, sequence or genome

Proper citation: Rfam (RRID:SCR_007891) Copy   

•   Source: SciCrunch Registry

http://locus.jouy.inra.fr/cgi-bin/lgbc/mapping/common/intro2.pl?BASE=goat

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. This website contains information about the mapping of the caprine genome. It contains loci list, phenes list, cartography, gene list, and other sequence information about goats. This website contains 731 loci, 271 genes, and 1909 homologue loci on 112 species. It also allows users to summit their own data for Goatmap. ARK-Genomics is not-for-profit and has collaborators from all over the world with an interest in farm animal genomics and genetics. ARK-Genomics was initially set up in 2000 with a grant awarded from the BBSRC IGF (Investigating Gene Function) initiative and from core resources of the Roslin Institute to provide a laboratory for automated analysis of gene expression using state-of-the-art genomic facilities. Since then, ARK-Genomics has expanded considerably, building up considerable expertise and resources.

Proper citation: GoatMap Database (RRID:SCR_008144) Copy   

•   Source: SciCrunch Registry

http://genome.wustl.edu/projects/detail/human-gut-microbiome/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 19,2022. Human Gut Microbiome Initiative (HGMI) seeks to provide simply annotated, deep draft genome sequences for 100 cultured representatives of the phylogenetic diversity documented by 16S rRNA surveys of the human gut microbiota. Humans are supra-organisms, composed of 10 times more microbial cells than human cells. Therefore, it seems appropriate to consider ourselves as a composite of many species - human, bacterial, and archaeal - and our genome as an amalgamation of human genes and the genes in ''our'' microbial genomes (''microbiome''). In the same sense, our metabolome can be considered to be a synthesis of co-evolved human and microbial traits. The total number of genes present in the human microbiome likely exceeds the number of our H. sapiens genes by orders of magnitude. Thus, without an understanding of our microbiota and microbiome, it not possible to obtain a complete picture of our genetic diversity and of our normal physiology. Our intestine is home to our largest collections of microbes: bacterial densities in the colon (up to 1 trillion cells/ml of luminal contents) are the highest recorded for any known ecosystem. The vast majority of phylogenetic types in the distal gut microbiota belong to just two divisions (phyla) of the domain Bacteria - the Bacteroidetes and the Firmicutes. Members of eight other divisions have also been identified using culture-independent 16S rRNA gene-based surveys. Metagenomic studies of complex microbial communities residing in our various body habitats are limited by the availability of suitable reference genomes for confident assignment of short sequence reads generated by highly parallel DNA sequencers, and by knowledge of the professions (niches) of community members. Therefore, HGMI, which represents a collaboration between Washington University''s Genome Center and its Center for Genome Sciences, seeks to provide simply annotated, deep draft genome sequences for 100 cultured representatives of the phylogenetic diversity documented by 16S rRNA surveys of the human gut microbiota.

Proper citation: Human Gut Microbiome Initiative (RRID:SCR_008137) Copy   

•   Source: SciCrunch Registry

http://www.gene-regulation.com/pub/databases.html

In an effort to strongly support the collaborative nature of scientific research, BIOBASE offers academic and non-profit organizations free access to reduced functionality versions of their products. TRANSFAC Professional provides gene regulation analysis solutions, offering the most comprehensive collection of eukaryotic gene regulation data. The professional paid subscription gives customers access to up-to-date data and tools not available in the free version. The public databases currently available for academic and non-profit organizations are: * TRANSFAC: contains data on transcription factors, their experimentally-proven binding sites, and regulated genes. Its broad compilation of binding sites allows the derivation of positional weight matrices. * TRANSPATH: provides data about molecules participating in signal transduction pathways and the reactions they are involved in, resulting in a complex network of interconnected signaling components.TRANSPATH focuses on signaling cascades that change the activities of transcription factors and thus alter the gene expression profile of a given cell. * PathoDB: is a database on pathologically relevant mutated forms of transcription factors and their binding sites. It comprises numerous cases of defective transcription factors or mutated transcription factor binding sites, which are known to cause pathological defects. * S/MARt DB: presents data on scaffold or matrix attached regions (S/MARs) of eukaryotic genomes, as well as about the proteins that bind to them. S/MARs organize the chromatin in the form of functionally independent loop domains gained increasing support. Scaffold or Matrix Attached Regions (S/MARs) are genomic DNA sequences through which the chromatin is tightly attached to the proteinaceous scaffold of the nucleus. * TRANSCompel: is a database on composite regulatory elements affecting gene transcription in eukaryotes. Composite regulatory elements consist of two closely situated binding sites for distinct transcription factors, and provide cross-coupling of different signaling pathways. * PathoSign Public: is a database which collects information about defective cell signaling molecules causing human diseases. While constituting a useful data repository in itself, PathoSign is also aimed at being a foundational part of a platform for modeling human disease processes.

Proper citation: Gene Regulation Databases (RRID:SCR_008033) Copy   

•   Source: SciCrunch Registry

http://ncv.unl.edu/Angelettilab/HPV/Database.html

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 August 23, 2016. The Human Papillomaviruses Database collects, curates, analyzes, and publishes genetic sequences of papillomaviruses and related cellular proteins. It includes molecular biologists, sequence analysts, computer technicians, post-docs and graduate research assistants. This Web site has two main branches. The first contains our four annual data books of papillomavirus information, called Human Papillomaviruses: A Compilation and Analysis of Nucleic Acid and Amino Acid Sequences. and the second contains papillomavirus genetic sequence data. There is also a New Items location where we store the latest changes to the database or any other current news of interest. Besides the compendium, we also provide genetic sequence information for papilloma viruses and related cellular proteins. Each year they publish a compendium of papillomavirus information called Human Papillomaviruses: A Compilation and Analysis of Nucleic Acid and Amino Acid Sequences. which can now be downloaded from this Web site.

Proper citation: HPV Sequence Database (RRID:SCR_008154) Copy   

•   Source: SciCrunch Registry

http://www.genomatix.de/

Genomatix is a privately held company that offers software, databases, and services aimed at understanding gene regulation at the molecular level representing a central part of systems biology. Its multilayer integrative approach is a working implementation of systems biology principles. Genomatix combines sequence analysis, functional promoter analysis, proprietary genome annotation, promoter sequence databases, comparative genomics, scientific literature data mining, pathway databases, biological network databases, pathway analysis, network analysis, and expression profiling into working solutions and pipelines. It also enables better understanding of biological mechanisms under different conditions and stimuli in the biological context of your data. Some of Genomatix'' most valuable assets are the strong scientific background and the years of experience in research & discovery as well as in development & application of scientific software. Their firsthand knowledge of all the complexities involved in the in-silico analysis of biological data makes them a first-rate partner for all scientific projects involving the evaluation of gene regulatory mechanisms. The Genomatix team has more than a decade of scientific expertise in the successful application of computer aided analysis of gene regulatory networks, which is reflected by more than 150 peer reviewed scientific publications from Genomatix'' scientists More than 35,000 researchers in industry and academia around the world use this technology. The software available in Genomatix are: - GenomatixSuite: GenomatixSuite is our comprehensive software bundle including ElDorado, Gene2Promoter, GEMS Launcher, MatInspector and MatBase. GenomatixSuite PE also includes BiblioSphere Pathway Edition. Chromatin IP Software - RegionMiner: Fast, extensive analysis of genomic regions. - ChipInspector: Discover the real power of your microarray data. Genome Annotation Software - ElDorado: Extended Genome Annotation. - Gene2Promoter: Retrieve & analyze promoters - GPD: The Genomatix Promoter Database, which is now included with Gene2Promoter. Knowledge Mining Software - BiblioSpere : The next level of pathway/genomics analysis. - LitInspector: Literature and pathway analysis for free. Sequence Analysis Software - GEMS Launcher: Our integrated collection of sequence analysis tools. - MalInspector: Search transcription factor binding sites - MatBase: The transcription factor knowledge base. Other (no registration required) Software - DiAlign: Multiple alignment of DNA/protein sequence. - Genomatix tools: Various small tools for sequence statistics, extraction, formatting, etc.

Proper citation: Genomatix Software: Understanding Gene Regulation (RRID:SCR_008036) Copy   

•   Source: SciCrunch Registry

http://www.animalgenome.org/pigs/nagrp.html

Database and resources on the pig genome.

Proper citation: U.S. Pig Genome Project (RRID:SCR_008151) Copy   

•   Source: SciCrunch Registry

http://csgr.pgml.uga.edu/

The objective of this project is to develop physical maps of the sorghum and rice genomes, based on BAC contigs that are cross-linked to each other and also to genetic maps and BAC islands for other large-genome crops and a library of ca. 50,000 expressed-sequence tags (EST''s) and corresponding cDNA clones, from diverse sorghum organs and developmental states. It also aims to improve understanding of genetic diversity and allelic richness that might be harbored ex situ (in gene banks) or in situ (in nature), and refine techniques for assesing allelic richness and Expedite data acquisition and utilization by a sound parnership between laboratory scientists and computational biologists. Specific goals of developing physical maps of sorghum and rice genomes include: -Enrich cross-links between sorghum and rice by mapping additional rice probes on sorghum. -Apply mapped DNA probes to macroarrays of sorghum, sugarcane, rice, and maize BACs. -Fingerprint 10x BAC libraries of Sorghum bicolor and S. propinquum. Libraries presently 3x and 6x respectively, to be expanded to 10x each. -Use fragment-matching (BAC-RF) method to determine locus-specificity in polyploids. - Contig assembly based on 1-3, plus rice BAC fingerprints generated under a separate Novartis project. -Evaluate methodology for rapid high-throughput assignment of new ESTs to BACs. -Conduct genomic sequencing in a region duplicated in both sorghum and arabidopsis. Selected BACs from sorghum(2), sugarcane, maize, rice, wheat. By improving the understanding of genetic diversity and allelic richness, the goal is to: -Sequence previously mapped sorghum DNA probes. -Discover & characterize 100 single nucleotide polymorphisms (SNPs) from cDNA markers. -Develop colorimetric high-throughput genotyping assays, and utilize to assess genetic diversity in geographically- and phenotypically-diverse sorghums. -Develop colorimetric high-throughput asssays for identifying phytochrome allelic variation, and apply these assays to a core collection representing a large set of genetic resources. -Support informatics group to streamline cataloging of DNA-level information relevant to large genetic resources collections. Lastly, the goals of expediting data acquisition and utilization include: -A new web-based resource for 3D-integration and visualization of structural and functional genomic data will be developed. -New sequence assembly and alignment software SABER (Sequence AssemBly in the presence of ERror), and PRIMAL(Practical RIgorous Multiple ALignment), will be evaluated with reference to existing standards (PHRED, PHRAP). -Specialized image processing and image analysis tools will be developed for acquistion and interpretation of qualitative and quantitative hybridization signals. To deal expeditiously with large volumes of data, parallel processing approaches will be investigated. Sponsors: * National Science Foundation (NSF) * National Sorghum Producers * University of Georgia Research Foundation (UGARF) * Georgia Research Alliance (GRA)

Proper citation: Comparative Saccharinae Genomics Resource (RRID:SCR_008153) Copy   

•   Source: SciCrunch Registry

http://genewindow.nci.nih.gov/

Software tool for pre- and post-genetic bioinformatics and analytical work, developed and used at the Core Genotyping Facility (CGF) at the National Cancer Institute. While Genewindow is implemented for the human genome and integrated with the CGF laboratory data, it stands as a useful tool to assist investigators in the selection of variants for study in vitro, or in novel genetic association studies. The Genewindow application and source code is publicly available for use in other genomes, and can be integrated with the analysis, storage, and archiving of data generated in any laboratory setting. This can assist laboratories in the choice and tracking of information related to genetic annotations, including variations and genomic positions. Features of GeneWindow include: -Intuitive representation of genomic variation using advanced web-based graphics (SVG) -Search by HUGO gene symbol, dbSNP ID, internal CGF polymorphism ID, or chromosome coordinates -Gene-centric display (only when a gene of interest is in view) oriented 5 to 3 regardless of the reference strand and adjacent genes -Two views, a Locus Overview, which varies in size depending on the gene or genomic region being viewed and, below it, a Sequence View displaying 2000 base pairs within the overview -Navigate the genome by clicking along the gene in the Locus Overview to change the Sequence View, expand or contract the genomic interval, or shift the view in the 5 or 3 direction (relative to the current gene) -Lists of available genomic features -Search for sequence matches in the Locus Overview -Genomic features are represented by shape, color and opacity with contextual information visible when the user moves over or clicks on a feature -Administrators can insert newly-discovered polymorphisms into the Genewindow database by entering annotations directly through the GUI -Integration with a Laboratory Information Management System (LIMS) or other databases is possible

Proper citation: GeneWindow (RRID:SCR_008183) Copy   

•   Source: SciCrunch Registry

http://www.osc.riken.jp/english/

Omics Science Center is aiming to develop a comprehensive system called Life Science Accelerator(LSA) for the advancement of omics research. The LSA is a comprehensive system consists of biological resources, human resources, technologies, know-how, and essential administrative ability. Ultimate goal of LSA is to support and accelerate the advancement in life science research. Omics is the comprehensive study of molecules in living organisms. The complete sequencing of genomes (the complete set of genes in an organism) has enabled rapid developments in the collection and analysis of various types of comprehensive molecular data such as transcriptomes (the complete set of gene expression data) and proteomes (the complete set of intracellular proteins). Fundamental omics research aims to link these omics data to molecular networks and pathways in order to advance the understanding of biological phenomena as systems at the molecular level.

Proper citation: RIKEN Omics Science Center (RRID:SCR_008241) Copy   

•   Source: SciCrunch Registry

http://flj.hinv.jp/

A human full-length cDNA sequence analysis database focused on mRNA varieties caused by variations of transcription start site (TSS) and splicing. Also available is ATGpr, a program for identifying the translational initiation codons in cDNA sequences. Data are derived from several full-length cDNA studies in Japan. Human gene number was estimated to be 20-25 thousand. However, the number of human mRNA varieties was predicted to be about 100 thousand. The varieties are thought to be caused by variations of TSS and splicing. In their previous human cDNA project, about 30 thousand of FLJ human full-length sequenced cDNAs were deposited to DDBJ/GenBank/EMBL, and they obtained about 1.4 million of 5''-end sequences (5''-EST) of FLJ full-length cDNAs from about 100 kinds of cDNA libraries consist of human tissues and cells constructed by oligo-capping method. The majority of the insert cDNA sizes were over 2 kb and the full-length rate of 5''-end was 90. And our FLJ cDNAs were covered about 80 of human genes. About 22 thousand of finished grades of full-length sequenced cDNAs were obtained in this project. The sequence analysis databases is focused on mRNA variations using human genome and cDNA sequences, FLJ full-length sequenced cDNAs, 5-ESTs of FLJ full-length cDNAs and other cDNA sequences described below. After those sequences were mapped onto the human genome sequences, clustering of the cDNA sequences were done based on the mapping results.

Proper citation: FLJ Human cDNA Database (RRID:SCR_008253) Copy   

•   Source: SciCrunch Registry

http://www.biodas.org

The Distributed Annotation System (DAS) defines a communication protocol used to exchange annotations on genomic or protein sequences. It is motivated by the idea that such annotations should not be provided by single centralized databases, but should instead be spread over multiple sites. Data distribution, performed by DAS servers, is separated from visualization, which is done by DAS clients. The advantages of this system are that control over the data is retained by data providers, data is freed from the constraints of specific organisations and the normal issues of release cycles, API updates and data duplication are avoided. DAS is a client-server system in which a single client integrates information from multiple servers. It allows a single machine to gather up sequence annotation information from multiple distant web sites, collate the information, and display it to the user in a single view. Little coordination is needed among the various information providers. DAS is heavily used in the genome bioinformatics community. Over the last years we have also seen growing acceptance in the protein sequence and structure communities. A DAS-enabled website or application can aggregate complex and high-volume data from external providers in an efficient manner. For the biologist, this means the ability to plug in the latest data, possibly including a user''s own data. For the application developer, this means protection from data format changes and the ability to add new data with minimal development cost. Here are some examples of DAS-enabled applications or websites for end users: :- Dalliance Experimental Web/Javascript based Genome Viewer :- IGV Integrative Genome Viewer java based browser for many genomes :- Ensembl uses DAS to pull in genomic, gene and protein annotations. It also provides data via DAS. :- Gbrowse is a generic genome browser, and is both a consumer and provider of DAS. :- IGB is a desktop application for viewing genomic data. :- SPICE is an application for projecting protein annotations onto 3D structures. :- Dasty2 is a web-based viewer for protein annotations :- Jalview is a multiple alignment editor. :- PeppeR is a graphical viewer for 3D electron microscopy data. :- DASMI is an integration portal for protein interaction data. :- DASher is a Java-based viewer for protein annotations. :- EpiC presents structure-function summaries for antibody design. :- STRAP is a STRucture-based sequence Alignment Program. Hundreds of DAS servers are currently running worldwide, including those provided by the European Bioinformatics Institute, Ensembl, the Sanger Institute, UCSC, WormBase, FlyBase, TIGR, and UniProt. For a listing of all available DAS sources please visit the DasRegistry. Sponsors: The initial ideas for DAS were developed in conversations with LaDeana Hillier of the Washington University Genome Sequencing Center.

Proper citation: Distributed Annotation System (RRID:SCR_008427) Copy   

•   Source: SciCrunch Registry

http://cgems.cancer.gov

The project began as a pilot study to identify inherited genetic susceptibility to prostate and breast cancer. CGEMS has developed into a robust research program involving genome-wide association studies (GWASs) for a number of cancers to identify common genetic variants that affect a person''s risk of developing cancer. In collaboration with extramural scientists, NCI''s Division of Cancer Epidemiology and Genetics (DCEG) has carried out genome-wide scans for breast, prostate, pancreatic, and lung cancers, while a GWAS of bladder cancer is currently underway. By making the data available to both intramural and extramural research scientists, as well as those in the private sector through rapid posting, NIH can leverage its resources to ensure that the dramatic advances in genomics are incorporated into rigorous population-based studies. Ultimately, findings from these studies may yield new preventive, diagnostic, and therapeutic interventions for cancer. Sponsors: This resource is supported by the U.S. National Institues Of Health.

Proper citation: CGEMS (RRID:SCR_008445) Copy   

•   Source: SciCrunch Registry