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http://taylor0.biology.ucla.edu/structureHarvester/
Web based program for collating results generated by program STRUCTURE. Provides assess and visualize likelihood values across multiple values of K and hundreds of iterations for easier detection of number of genetic groups that best fit data. Reformats data for use in downstream programs, such as CLUMPP.It is complement for using software Structure in genetics population. Website and program for visualizing STRUCTURE output and implementing Evanno method., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: Structure Harvester (RRID:SCR_017636) Copy
http://chemrich.fiehnlab.ucdavis.edu/
Software tool for chemical similarity enrichment analysis of metabolomics datasets. Used in studies to uncover biological mechanisms in organisms under genetic or environmental stress in system biology manner or finding risk factors for chronic diseases in exposome wise association studies using blood specimens. Allows users to realize pathway analysis.
Proper citation: ChemRICH (RRID:SCR_017609) Copy
THIS RESOURCE IS NO LONGER IN SERVICE, documented on September 23, 2013. Software application / data analysis service where one can enter the alleles of commonly used STR by clicking the mouse. The algorithm calculates the paternity index and the Essen-Moeller probability of kinship for the deficiency- and the trio case. Everybody can use the network-software online after registering. The usage on the internet is free. Academic users can ask me to unlock an option to display the details (formulas/frequencies etc.) and to have an export-funktion to MS Word. The program is in German and (non-professional) English. An expansion to other languages is easy, if somebody helps us with the translation. For those who are interested to have the software running on their own intranet (for database security reasons) an individual agreement can be found. (entry from Genetic Analysis Software) (German version is: http://www.allelix.de)
Proper citation: ALLELIX (RRID:SCR_009115) Copy
Web-based tool that allows users to view comparisons of genetic and physical maps. The package also includes tools for curating map data. (entry from Genetic Analysis Software)
Proper citation: CMAP (RRID:SCR_009034) Copy
Collects and provides data on the human genome and epigenome to facilitate genetic studies of type 2 diabetes and its complications. A component of the AMP T2D consortium, which includes the National Institute for Diabetes and Digestive and Kidney Diseases (NIDDK) and an international collaboration of researchers.
Proper citation: Diabetes Epigenome Atlas (RRID:SCR_016441) Copy
http://sleepdisordergenetics.org
Software platform for accelerating genetic discoveries for sleep disturbance and circadian traits.
Proper citation: Sleep Disorder Knowledge Portal (RRID:SCR_016611) Copy
Portal to map and identify genetic variants that predispose to type 2 diabetes mellitus (T2D) or are responsible for variability in diabetes-related quantitative traits. Used for analysis of affected-sibling-pair (ASP) families in Finland, and association fine mapping based on these family members and additional T2D cases and controls.
Proper citation: FUSION study (RRID:SCR_016580) Copy
Web tool to search multiple public variant databases simultaneously and provide a unified interface to facilitate the search process. Used for integration of human and model organism genetic resources to facilitate functional annotation of the human genome. Used for analysis of human genes and variants by cross-disciplinary integration of records available in public databases to facilitate clinical diagnosis and basic research.
Proper citation: MARRVEL (RRID:SCR_016871) Copy
https://software.broadinstitute.org/software/discovar/blog/
Software tool for variant calling with reference and de novo assembly of genomes. The heart of DISCOVAR is a de novo genome assembler which can generate de novo assemblies for both large and small genomes.
Proper citation: Discovar assembler (RRID:SCR_016755) Copy
https://deepblue.mpi-inf.mpg.de/
Central data access hub for large collections of epigenomic data. It organizes data from different sources using controlled vocabularies and ontologies. Data Server for storing, organizing, searching, and retrieving genomic and epigenomic data, handling associated metadata, and to perform different types of analysis.
Proper citation: Deep Blue Epigenomic Data Server (RRID:SCR_017490) Copy
Software package for advanced Bayesian evolutionary analysis by sampling trees. Used for phylogenetics, population genetics and phylodynamics. Program for Bayesian phylogenetic analysis of molecular sequences. Estimates rooted, time measured phylogenies using strict or relaxed molecular clock models. Framework can be extended by third parties. Comprised of standalone programs including BEAUti, BEAST, MASTER, RBS, SNAPP, MultiTypeTree, BDSKY, LogAnalyser, LogCombiner, TreeAnnotator, DensiTree and package manager.
Proper citation: BEAST2 (RRID:SCR_017307) Copy
http://www.mirecc.va.gov/visn6/
The VISN 6 MIRECC is organized as a translational medicine multi-site center focused on post deployment mental health issues. The overarching goals are improving clinical assessment and treatment and development of novel interventions through basic and clinical research. This MIRECC aims: (1) To determine whether early intervention in post-deployment mental health is effective in forestalling the development or decreasing the severity of post-deployment mental illness, (2) To determine what neuroimaging, genetic, neurocognitive, or other characteristics predict the development of post-deployment mental illness, and (3) To assess the longitudinal course of post-deployment mental illness.
Proper citation: Mid-Atlantic (VISN 6) Mental Illness Research, Education and Clinical Center (RRID:SCR_008077) Copy
An animated primer on the basics of DNA, genes, and heredity organized around three key concepts: Classical Genetics, Molecules of Genetics, and Genetic Organization and Control. The science behind each concept is explained by: animation, image gallery, video interviews, problem, biographies, and links.
Proper citation: DNA From The Beginning: AN Animated Primer on the Basics of DNA, Genes, and Heredity (RRID:SCR_008028) Copy
http://www.projects.roslin.ac.uk/cdiv/
THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. The objective of the project is the standardization of micro-satellite markers used within participating laboratories, use of DNA markers to define genetic diversity and to enable monitoring of breeds to promote conservation programs where required, and the determination of diversity present in rare and local breeds across Europe. The blood typing laboratories are now beginning to use micro-satellite markers as an alternative to serology for parentage verification, and are selecting a common set to be used from the several hundred micro-satellite markers available that cover the bovine genome, produced as part of the Bovine genome mapping project (See BovMaP). Work with micro-satellite markers has shown that they are valuable tools for examining genetic diversity and phylogeny in many species. However, for work carried out in different laboratories to be comparable, it is essential that the same markers are used. To maintain the compatibility of data generated by the various typing labs, it is essential that all laboratories adopt the same markers and typing protocols. It is therefore of paramount importance that the blood typing laboratories and research labs that are examining the genetic structure of the cattle populations adopt a common panel of the best micro-satellite markers available. Some pilot comparative work has been undertaken through the International Society for Animal Genetics, but so far this has only involved the blood typing laboratories. One objective of this project is to facilitate the comparison of the micro-satellite markers currently in use in the different types of laboratory and determine the efficiency of the markers available in revealing genetic differences within and among breeds. It will also be important to compare the use of markers in different laboratories to determine how robust they are and how easily results can be compared. From comparison of the markers, those that are most suitable will be selected to form a panel which will be recommended for pedigree validation and genetic surveys. Cattle are an important source of food in Europe, and intense selection has resulted in the development of specialized breeds. Selection for high-producing dairy cattle has been successful, but one associated drawback is that the cattle population, both in Europe and North America, has been skewed dramatically towards one breed, the Holstein/Friesian. So there has been a decline in the number of individuals of other breeds, and hence a general erosion of the genetic base of the cattle population. The progressive move towards the North American-type Holstein animals has also resulted in the requirement for high input/high output farming and intensive management schemes. The impact of this on the environment has been significant, e.g. pollution problems arising from the need for high nitrogen fertilizers to produce sufficient high quality fodder, and disposal problems associated with slurry waste. Poorer areas of the community have been unable to compete with such farming systems, and are more suited to low input/low output farming using traditional stock. It is however the future perspective that is of greatest concern. It is impossible to predict requirements for cattle production - quality, production type, management systems, etc. The ability to switch rapidly to alternative production will be dependent on the genetic base of the population available to selection programs. It is therefore essential to maintain the greatest genetic diversity possible in the cattle population. Whilst current farming practices are perceived to be both efficient and acceptable, the breeds less favored by commercial farmers will dwindle. It is therefore important that on an European scale efficient management of these breeds maintains the widest genetic base possible. This project aims to carry out a survey of the current genetic base of the European cattle population and to provide the tools to assist breeding programs to maintain a broad base. The blood typing laboratories are now beginning to use micro-satellite markers as an alternative to serology for parentage verification, and are selecting a common set to be used from the several hundred micro-satellite markers available that cover the bovine genome, produced as part of the Bovine genome mapping project. Early work to measure genetic diversity used blood groups to show differences between breeds and the diversity present. Unfortunately, the number of loci available are limited, with only the B system being sufficiently polymorphic to be really useful. However, since there is a wealth of information available from such typing, this information can be used to estimate changes in the genetic structure of cattle populations across Europe over the past twenty years. More recently mini-satellite probes have been used to generate ''genetic fingerprints'' which have been used to show differences between individuals. Such fingerprints have been used to estimate genetic diversity - the greater the number of bands revealed by the fingerprint being equated with greater diversity. This is valid within limits. The main disadvantage of the fingerprint approach is that the chromosomal location and number of loci being sampled, and so the proportion of the genome examined, is unknown. The allelic bands on the gel cannot be easily identified, so allele inheritance cannot be addressed making it impossible to trace ancestry. Through the EC funded BovMaP project, large numbers of highly polymorphic micro-satellite markers have become available, which are being mapped on the bovine genome. These markers are particularly suited to measuring genetic diversity, and markers can be selected to cover the entire genome.
Proper citation: CaDBase: Genetic diversity in cattle (RRID:SCR_008146) Copy
http://locus.jouy.inra.fr/cgi-bin/bovmap/intro.pl
THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. Database containing information on the cattle genome comprising loci list, phenes list, homology query, cattle maps, gene list, and chromosome homology. The objective of BovMap is to develop a set of anchored loci for the cattle genome map. In total, 58 clones were hybridized with chromosomes and identified loci on 22 of the 31 different bovine chromosomes. Three clones contained satellite DNA. Two or more markers were placed on 12 chromosomes. Sequencing of the microsatellites and flanking regions was performed directly from 43 cosmids, as previously reported. Primers were developed for 39 markers and used to describe the polymorphism associated with the corresponding loci. Users are also allowed to summit their own data for Bovmap. An integrated cytogenetic and meiotic map of the bovine genome has also been developed around the Bovmap database. One objective that Bovmap uses as the mapping strategy for the bovine genome uses large insert clones as a tool for physical mapping and as a source of highly polymorphic microsatellites for genetic typing.
Proper citation: BovMap Database (RRID:SCR_008145) Copy
Merger of the Max Planck Institute of Neurobiology and the Max Planck Institute of Ornithology and has been renamed to Circuits - Computation – Models. Department devoted to the study of how the brain computes to understand neural information processing at the level of individual neurons and small neural circuits.
Proper citation: Max Planck Institute for Biological Intelligence Circuits - Computation – Models (RRID:SCR_008048) Copy
http://www.scripps.edu/np/inia/index.html
Consortium set out to identify the molecular, cellular, and behavioral neuroadaptations that occur in the brain reward circuits associated with the extended amygdala and its connections. It is hypothesized that genetic differences and/or neuroadaptations in this circuitry are responsible for the individual differences in vulnerability to the excessive consumption of alcohol. Chronic exposure to alcohol results in neuroadaptive phenomena, including tolerance, sensitization, dependence, withdrawal, loss of control of drinking, and relapse that contribute to the development of excessive alcohol consumption. The INIA has the following goals: 1) To establish animal models to study specific neurobiological targets for vulnerability that lead to excessive consumption of alcohol at the molecular, cellular and neural circuit level of analysis, 2) To identify specific clusters of genes whose expression is regulated by alcohol and which are responsible for any given model of excessive alcohol consumption using gene expression arrays, differential display, mutagenesis directed at specific brain areas, and the development of new informatics tools to analyze and interpret gene expression, cellular circuitry and brain circuitry data with the use of transgenic and knockout approaches, and 3) To attract new and innovative investigators to the field of alcohol research by recruiting individuals for development of U01 grants and pilot projects and by developing online interactive capacity among INIA scientists and others, and by making the neuroinformatics integrated data sets accessible, searchable and interactive with other databases for all scientists interested in alcoholism research. The structure of INIA is envisioned as two domains, Dependence-induced drinking and Binge drinking, comprised of multiple U01 research grants. The flow of information within each domain moves from molecular, to cellular, to neurocircuitry levels of analysis. These U01s share information with the core facilities, which act as data depositories. The Administrative Core coordinates the flow of information among the Domains and Cores and disseminates the information back to the U01s. A Pilot Project program will identify exciting new areas for research and the continual recruitment of new investigators to the alcohol field. The INIA program is directed by an Administrative Core in close cooperation with the Animal Models, Gene Array and Neurocircuitry Cores via a Steering Committee and with the continual advice of the Scientific Advisory Committee.
Proper citation: Integrative Neuroscience Initiative on Alcoholism (RRID:SCR_008042) Copy
https://wiki.med.harvard.edu/SysBio/Megason/GoFigure
GoFigure is a software platform for quantitating complex 4d in vivo microscopy based data in high-throughput at the level of the cell. A prime goal of GoFigure is the automatic segmentation of nuclei and cell membranes and in temporally tracking them across cell migration and division to create cell lineages. GoFigure v2.0 is a major new release of our software package for quantitative analysis of image data. The research focuses on analyzing cells in intact, whole zebrafish embryos using 4d (xyzt) imaging which tends to make automatic segmentation more difficult than with 2d or 2d+time imaging of cells in culture. This resource has developed an automatic segmentation pipeline that includes ICA based channel unmixing, membrane nuclear channel subtraction, Gaussian correlation, shape models, and level set based variational active contours. GoFigure was designed to meet the challenging requirements of in toto imaging. In toto imaging is a technology that we are developing in which we seek to track all the cell movements and divisions that form structures during embryonic development of zebrafish and to quantitate protein expression and localization on top of this digital lineage. For in toto imaging, GoFigure uses zebrafish embryos in which the nuclei and cell membranes have been marked with 2 different color fluorescent proteins to allow cells to be segmented and tracked. A transgenic line in a third color can be used to mark protein expression and localization using a genetic approach that this resource developed called FlipTraps or using traditional transgenic approaches. Embryos are imaged using confocal or 2-photon microscopy to capture high-resolution xyzt image sets used for cell tracking. The GoFigure GUI will provide many tools for visualization and analysis of bioimages. Since fully automatic segmentation of cells is never perfect, GoFigure will provide easy to use tools for semi-automatically and manually adding, deleting, and editing traces in 2d (figures-xy, xz, or yz), 3d (meshes- xyz), 4d (tracks- xyzt) and 4d+cell division (lineages). GoFigure will also provide a number of views into complex image data sets including 3d XYZ and XYT image views, tabular list views of traces, histograms, and scattergrams. Importantly, all these views will be linked together to allow the user to explore their data from multiple angles. Data will be easily sorted and color-coded in many ways to explore correlations in higher dimensional data. The GoFigure architecture is designed to allow additional segmentation, visualization, and analysis filters to be plugged in. Sponsors: GoFigure is developed by Harvard University., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: Harvard Medical School, Department of Systems Biology: The Megason Lab -GoFigure Software (RRID:SCR_008037) Copy
http://www.vet.ohio-state.edu/211.htm
Laboratory animals are used in nearly half of all research projects supported by the National Institutes of Health. Significant needs exist at the national level for skilled scientists trained to work with and interpret the data generated from the use of rodent animal models. In response to this national need a research training program has been established through funding by the National Centers for Research Resources to provide an environment for veterinarians (D.V.M. or V.M.D.) and D.V.M./Ph.D.''s to effectively utilize mouse models of human disease. Specifically, veterinarian scientists are trained in state of-the-art molecular and cellular techniques to systematically evaluate the mechanistic pathobiology and phenotype of experimental mouse models of human disease. The training program is coordinated through an established graduate program in the College of Veterinary Medicine, Department of VeterinaryBiosciences and supported by a unified group of basic and clinical scientists with ongoing collaborative programs at The Ohio State University and Children''s Hospital. The scientists have expertise in endocrinology, infectious disease, genetics, oncology, molecular biology, immunology, physiology, biochemistry, and pathology. Trainees gain knowledge and skills to fully understand and evaluate pathophysiologic alterations of murine models of human disease through both didactic coursework and applied training in pathology and molecular biology. In addition, trainees interact with our multidisciplinary faculty to identify the range of research problems that use murine models. They acquaint themselves with the ongoing basic and clinical research studies in the laboratories and clinical sites of the participating faculty, and select a research problem that utilizes a murine model for endpoint evaluation. Following the selection of a preceptor and research problem, the trainee participates in the design and performance of experiments, as well as analysis and presentation of data regarding a murine model. Trainees develop skills in clinical, gross, and histologic pathology, molecular and immunologic techniques, and use transgenic and immunodeficient mouse models to identify and characterize alterations in embryonic and postnatal development. Therefore, trainees acquire a broad background in molecular biology, genetics, pathology, laboratory animal medicine, as well as research design methodology to fulfill national needs in the development of skilled scientists in mouse pathobiology. :Sponsors: Mouse Pathology Training Grant is funded by the National Centers for Research Resources.
Proper citation: Mouse Pathology Training Grant (RRID:SCR_008300) Copy
http://depts.washington.edu/adrcweb/
Research center investigating the basic mechanisms underlying the development of Alzheimer's disease and related disorders, directing particular attention to biomarkers and experimental new treatments. They also continue to search for genetic risk factors underlying Alzheimer's disease (AD). Their main priorities are to find causes, effective treatments, and prevention strategies. Their investigators also are partnering with other Alzheimer's Centers across the country to evaluate promising new medications and other treatments for AD. The ultimate goal of their basic and clinical studies is to improve patient care and function, and improve the quality of life for both the patient and the caregiver. ADRC Cores: * Administration * Clinical Core * Satellite Core * Data Management & Biostatistics * Neuropathology Core * Education & Information Transfer * Genetics
Proper citation: University of Washington Alzheimers Disease Research Center (RRID:SCR_008814) Copy
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