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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://www.sanger.ac.uk/Projects/Microbes/

This website includes a list of projects that the Sanger Institute is currently working on or completed. All projects consist of the genomic sequencing of different bacteria. Each description of the bacteria includes its classification, a description, and the types of diseases that the bacteria is likely to cause. The Sanger Institute bacterial sequencing effort is concentrated on pathogens and model organisms. Data is accessible in a number of ways; for each organism there is a BLAST server, allowing users to search the sequences with their own query and retrieve the matching contigs. Sequences can also be downloaded directly by FTP. Data is accessible in a number of ways; for each organism there is a BLAST server, allowing you to search the sequences with your own query and retrieve the matching contigs. Sequences can also be downloaded directly by FTP. The primary sequence viewer and annotation tool, Artemis is available for download. This is a portable Java program which is used extensively within the Microbial Genomes group for the analysis and annotation of sequence data from cosmids to whole genomes. The Artemis Comparison Tool (ACT) is also useful for interactive viewing of the comparisons between large and small sequences.

Proper citation: Bacterial Genomes (RRID:SCR_008141) 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://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.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://bioinf.uni-greifswald.de/augustus/

Software for gene prediction in eukaryotic genomic sequences. Serves as a basis for further steps in the analysis of sequenced and assembled eukaryotic genomes.

Proper citation: Augustus (RRID:SCR_008417) Copy   

•   Source: SciCrunch Registry

http://www.lajollaneuroscience.org/

Our NINDS Center Core Grant supports centralized resources and facilities shared by investigators with existing NINDS-funded research projects. Our Center is composed of three research cores, each of which will enrich the effectiveness of ongoing research, and promote new research directions. The three Core facilities support Electrophysiology, Neuropathology / Histology, and High-Throughput/High-Content Chemical and Genomic Library screening. By making these important Core Services available to the local Neuroscience community, the La Jolla Neurosciences Program hopes to promote the study of how the nervous system works and develop treatments for nervous system diseases. The cores and their services are available to La Jolla neuroscientists. Core services are available to NINDS-supported neuroscience projects from local investigators as well as young neuroscientists prior to obtaining their first NIH-funded grant. * Electrophysiology: SBMRI Electrophysiology ** The Electrophysiology Core consists of the Sanford-Burnham Electrophysiology Facility. This facility can perform patch-clamp intracellular and extracellular field recordings on a range of material including cultured cells and brain slices. The Sanford-Burnham facility emphasizes electrophysiological analysis of cultured cells and the detailed electrical properties of channels, receptors and recombinant proteins expressed in Xenopus oocytes or mammalian cells. * Neuropathology: UCSD Neuropathology ** The Neuropathology laboratory applies immunocytochemistry, neurochemistry, molecular genetics, transgenic models of disease, and imaging by scanning laser confocal microscopy to analysis of neurological disease in animal models. * Chemical Library Screening: SBIMR Assay Development, SBIMR Chemical Library Screening, SBIMR Cheminformatics, SBIMR High-content Screening ** The Chemical Library Screening core offers high-throughput screening (HTS) of biochemical and cell-based array using traditional HTS readouts and automated microscopy for high-content screening (HCS)> These facilities also offer array development and screening, as well as cheminformatics and medicinal chemistry., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 15,2026.

Proper citation: La Jolla Interdisciplinary Neurosciences Center (RRID:SCR_002772) Copy   

•   Source: SciCrunch Registry

http://www.macaque.org/

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 on June 8, 2020.Macaque genomic and proteomic resources and how they are providing important new dimensions to research using macaque models of infectious disease. The research encompasses a number of viruses that pose global threats to human health, including influenza, HIV, and SARS-associated coronavirus. By combining macaque infection models with gene expression and protein abundance profiling, they are uncovering exciting new insights into the multitude of molecular and cellular events that occur in response to virus infection. A better understanding of these events may provide the basis for innovative antiviral therapies and improvements to vaccine development strategies.

Proper citation: Macaque.org (RRID:SCR_002767) Copy   

•   Source: SciCrunch Registry

http://www.ambystoma.org/

Portal that supports Ambystoma-related research and educational efforts. It is composed of several resources: Salamander Genome Project, Ambystoma EST Database, Ambystoma Gene Collection, Ambystoma Map and Marker Collection, Ambystoma Genetic Stock Center, and Ambystoma Research Coordination Network.

Proper citation: Sal-Site (RRID:SCR_002850) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/cancer/software/genepattern

A powerful genomic analysis platform that provides access to hundreds of tools for gene expression analysis, proteomics, SNP analysis, flow cytometry, RNA-seq analysis, and common data processing tasks. A web-based interface provides easy access to these tools and allows the creation of multi-step analysis pipelines that enable reproducible in silico research.

Proper citation: GenePattern (RRID:SCR_003201) Copy   

•   Source: SciCrunch Registry

http://www.loni.usc.edu/BIRN/Projects/Mouse/

Animal model data primarily focused on mice including high resolution MRI, light and electron microscopic data from normal and genetically modified mice. It also has atlases, and the Mouse BIRN Atlasing Toolkit (MBAT) which provides a 3D visual interface to spatially registered distributed brain data acquired across scales. The goal of the Mouse BIRN is to help scientists utilize model organism databases for analyzing experimental data. Mouse BIRN has ended. The next phase of this project is the Mouse Connectome Project (https://www.nitrc.org/projects/mcp/). The Mouse BIRN testbeds initially focused on mouse models of neurodegenerative diseases. Mouse BIRN testbed partners provide multi-modal, multi-scale reference image data of the mouse brain as well as genetic and genomic information linking genotype and brain phenotype. Researchers across six groups are pooling and analyzing multi-scale structural and functional data and integrating it with genomic and gene expression data acquired from the mouse brain. These correlated multi-scale analyses of data are providing a comprehensive basis upon which to interpret signals from the whole brain relative to the tissue and cellular alterations characteristic of the modeled disorder. BIRN's infrastructure is providing the collaborative tools to enable researchers with unique expertise and knowledge of the mouse an opportunity to work together on research relevant to pre-clinical mouse models of neurological disease. The Mouse BIRN also maintains a collaborative Web Wiki, which contains announcements, an FAQ, and much more.

Proper citation: Mouse Biomedical Informatics Research Network (RRID:SCR_003392) Copy   

•   Source: SciCrunch Registry

http://tagcleaner.sourceforge.net/

A software tool which can automatically detect and efficiently remove tag sequences from genomic and metagenomic datasets.

Proper citation: TagCleaner (RRID:SCR_011846) Copy   

•   Source: SciCrunch Registry

https://www.q2labsolutions.com/genomics-laboratories

Core provides whole genome to focused set gene expression and genotyping assays along with DNA sequencings services, sequence enrichment technologies and bioinformatics support. Platforms utilized include Affymetrix GeneChip, Agilent Sure Select, Fluidigm Access Arrays, Illumina BeadChip, iScan, Genome Analyzer and Hi-Seq, RainDance Technologies RDT 1000 and, the Pacific Biosciences PacBio RS. Expression Analysis offers solutions for challenging specimens such as whole blood and FFPE tissues, as well as nucleic acid isolation and data analysis services.

Proper citation: Q Squared Solutions Expression Analysis (RRID:SCR_012497) Copy   

•   Source: SciCrunch Registry

http://www.viprbrc.org/brc/home.do?decorator=vipr

Provides searchable public repository of genomic, proteomic and other research data for different strains of pathogenic viruses along with suite of tools for analyzing data. Data can be shared, aggregated, analyzed using ViPR tools, and downloaded for local analysis. ViPR is an NIAID-funded resource that support the research of viral pathogens in the NIAID Category A-C Priority Pathogen lists and those causing (re)emerging infectious diseases. It provides a dedicated gateway to SARS-CoV-2 data that integrates data from external sources (GenBank, UniProt, Immune Epitope Database, Protein Data Bank), direct submissions, analysis pipelines and expert curation, and provides a suite of bioinformatics analysis and visualization tools for virology research.

Proper citation: Virus Pathogen Resource (ViPR) (RRID:SCR_012983) Copy   

•   Source: SciCrunch Registry

http://PlasmoDB.org

Functional genomic database for malaria parasites. Database for Plasmodium spp. Provides resource for data analysis and visualization in gene-by-gene or genome-wide scale. PlasmoDB 5.5 contains annotated genomes, evidence of transcription, proteomics evidence, protein function evidence, population biology and evolution data. Data can be queried by selecting from query grid or drop down menus. Results can be combined with each other on query history page. Search results can be downloaded with associated functional data and registered users can store their query history for future retrieval or analysis.Key community database for malaria researchers, intersecting many types of laboratory and computational data, aggregated by gene.

Proper citation: PlasmoDB (RRID:SCR_013331) Copy   

•   Source: SciCrunch Registry

http://www.dkfz.de/en/epidemiologie-krebserkrankungen/software/software.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 24,2023. Software program that performs estimation of power and sample sizes required to detect genetic and environmental main, as well as gene-environment interaction (GxE) effects in indirect matched case-control studies (1:1 matching). When the hypothesis of GxE is tested, power/sample size will be estimated for the detection of GxE, as well as for the detection of genetic and environmental marginal effects. Furthermore, power estimation is implemented for the joint test of genetic marginal and GxE effects (Kraft P et al., 2007). Power and sample size estimations are based on Gauderman''s (2002) asymptotic approach for power and sample size estimations in direct studies of GxE. Hardy-Weinberg equilibrium and independence of genotypes and environmental exposures in the population are assumed. The estimates are based on genotypic codes (G=1 (G=0) for individuals who carry a (non-) risk genotype), which depend on the mode of inheritance (dominant, recessive, or multiplicative). A conditional logistic regression approach is used, which employs a likelihood-ratio test with respect to a biallelic candidate SNP, a binary environmental factor (E=1 (E=0) in (un)exposed individuals), and the interaction between these components. (entry from Genetic Analysis Software)

Proper citation: PIAGE (RRID:SCR_013124) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.ust.hk/BOOST.html

Software application (entry from Genetic Analysis Software) for a method for detecting gene-gene interactions. It allows examining all pairwise interactions in genome-wide case-control studies.

Proper citation: BOOST (RRID:SCR_013133) Copy   

•   Source: SciCrunch Registry

http://folk.uio.no/thoree/FEST/

An R package for simulations and likelihood calculations of pair-wise family relationships using DNA marker data. (entry from Genetic Analysis Software)

Proper citation: R/FEST (RRID:SCR_013347) Copy   

•   Source: SciCrunch Registry

http://www.i2b2.org

i2b2 (Informatics for Integrating Biology and the Bedside) is an NIH-funded National Center for Biomedical Computing based at Partners HealthCare System. The i2b2 Center is developing a scalable informatics framework that will enable clinical researchers to use existing clinical data for discovery research and, when combined with IRB-approved genomic data, facilitate the design of targeted therapies for individual patients with diseases having genetic origin. For some resources (e.g. software) the use of the resource requires accepting a specific (e.g. OpenSource) license.

Proper citation: Informatics for Integrating Biology and the Bedside (RRID:SCR_013629) Copy   

•   Source: SciCrunch Registry

http://www.euratrans.eu/

The European large-scale functional genomics in the rat for translational research (EURATRANS) consortium brings together investigators who will use next-generation sequencing technologies to generate genomic, transcriptomic and epigenomic datasets. The goal is to create quantitative metabonomic and proteomic datasets to give significant depth of coverage, at multiple levels, across pathophysiological phenotypes. The aim is to enable insights into disease mechanisms, through an integrative, cross-disciplinary approach to understanding large-scale functional genomic datasets in rats and humans.

Proper citation: European large-scale functional genomics in the rat for translational research (EURATRANS) (RRID:SCR_013697) Copy   

•   Source: SciCrunch Registry