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http://www.nervenet.org/main/dictionary.html

A mouse-related portal of genomic databases and tables of mouse brain data. Most files are intended for you to download and use on your own personal computer. Most files are available in generic text format or as FileMaker Pro databases. The server provides data extracted and compiled from: The 2000-2001 Mouse Chromosome Committee Reports, Release 15 of the MIT microsatellite map (Oct 1997), The recombinant inbred strain database of R.W. Elliott (1997) and R. W. Williams (2001), and the Map Manager and text format chromosome maps (Apr 2001). * LXS genotype (Excel file): Updated, revised positions for 330 markers genotyped using a panel of 77 LXS strain. * MIT SNP DATABASE ONLINE: Search and sort the MIT Single Nucleotide Polymorphism (SNP) database ONLINE. These data from the MIT-Whitehead SNP release of December 1999. * INTEGRATED MIT-ROCHE SNP DATABASE in EXCEL and TEXT FORMATS (1-3 MB): Original MIT SNPs merged with the new Roche SNPs. The Excel file has been formatted to illustrate SNP haplotypes and genetic contrasts. Both files are intended for statistical analyses of SNPs and can be used to test a method outlined in a paper by Andrew Grupe, Gary Peltz, and colleagues (Science 291: 1915-1918, 2001). The Excel file includes many useful equations and formatting that will help in navigating through this large database and in testing the in silico mapping method. * Use of inbred strains for the study of individual differences in pain related phenotypes in the mouse: Elissa J. Chesler''s 2002 dissertation, discussing issues relevant to the integration of genomic and phenomic data from standard inbred strains including genetic interactions with laboratory environmental conditions and the use of various in silico inbred strain haplotype based mapping algorithms for QTL analysis. * SNP QTL MAPPER in EXCEL format (572 KB, updated January 2002 by Elissa Chesler): This Excel workbook implements the Grupe et al. mapping method and outputs correlation plots. The main spreadsheet allows you to enter your own strain data and compares them to haplotypes. Be very cautious and skeptical when using this spreadsheet and the technique. Read all of the caveates. This excel version of the method was developed by Elissa Chesler. This updated version (Jan 2002) handles missing data. * MIT SNP Database (tab-delimited text format): This file is suitable for manipulation in statistics and spreadsheet programs (752 KB, Updated June 27, 2001). Data have been formatted in a way that allows rapid acquisition of the new data from the Roche Bioscience SNP database. * MIT SNP Database (FileMaker 5 Version): This is a reformatted version of the MIT Single Nucleotide Polymorphism (SNP) database in FileMaker 5 format. You will need a copy of this application to open the file (Mac and Windows; 992 KB. Updated July 13, 2001 by RW). * Gene Mapping and Map Manager Data Sets: Genetic maps of mouse chromosomes. Now includes a 10th generation advanced intercross consisting of 500 animals genetoyped at 340 markers. Lots of older files on recombinant inbred strains. * The Portable Dictionary of the Mouse Genome, 21,039 loci, 17,912,832 bytes. Includes all 1997-98 Chromosome Committee Reports and MIT Release 15. * FullDict.FMP.sit: The Portable Dictionary of the Mouse Genome. This large FileMaker Pro 3.0/4.0 database has been compressed with StuffIt. The Dictionary of the Mouse Genome contains data from the 1997-98 chromosome committee reports and MIT Whitehead SSLP databases (Release 15). The Dictionary contains information for 21,039 loci. File size = 4846 KB. Updated March 19, 1998. * MIT Microsatellite Database ONLINE: A database of MIT microsatellite loci in the mouse. Use this FileMaker Pro database with OurPrimersDB. MITDB is a subset of the Portable Dictionary of the Mouse Genome. ONLINE. Updated July 12, 2001. * MIT Microsatellite Database: A database of MIT microsatellite loci in the mouse. Use this FileMaker Pro database with OurPrimersDB. MITDB is a subset of the Portable Dictionary of the Mouse Genome. File size = 3.0 MB. Updated March 19, 1998. * OurPrimersDB: A small database of primers. Download this database if you are using numerous MIT primers to map genes in mice. This database should be used in combination with the MITDB as one part of a relational database. File size = 149 KB. Updated March 19, 1998. * Empty copy (clone) of the Portable Dictionary in FileMaker Pro 3.0 format. Download this file and import individual chromosome text files from the table into the database. File size = 231 KB. Updated March 19, 1998. * Chromosome Text Files from the Dictionary: The table lists data on gene loci for individual chromosomes.

Proper citation: Mouse Genome Databases (RRID:SCR_007147) Copy   

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http://www.aneurist.org/

Project focused on cerebral aneurysms and provides integrated decision support system to assess risk of aneurysm rupture in patients and to optimize their treatments. IT infrastructure has been developeded for management and processing of vast amount of heterogeneous data acquired during diagnosis.

Proper citation: aneurIST (RRID:SCR_007427) Copy   

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https://cran.r-project.org/web/packages/tdthap/index.html

Software package for TDT with extended haplotypes in the R language. R is the public domain dialect of S. It should be possible to port this library to the commercial Splus product. The main problem would be translation of the help files. (entry from Genetic Analysis Software)

Proper citation: R/TDTHAP (RRID:SCR_007625) Copy   

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http://wwwmgs.bionet.nsc.ru/mgs/gnw/about.shtml

GeneNetWorks is designed for accumulation of experimental data, data navigation, data analysis, and analysis of dependencies in the field of gene expression regulation. It integrates the databases and programs for processing the data about structure and function of DNA, RNA, and proteins, together with the other information resources important for gene expression description. The unique property of above described system is that all the resources within the system GeneNetWorks are divided according to the natural hierarchy of molecular genetic systems and has the following levels: (1) DNA; (2) RNA; (3) proteins; and (4) gene networks. Each module contains: 1) experimental data represented as a database or some sample; 2) program for data analysis; 3) results of an automated data processing; 4) tools for the graphical representation of these data and the results of the data analyses.

Proper citation: GeneNetWorks (RRID:SCR_008034) Copy   

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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   

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http://www.jax.org/imr/index.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 08, 2012. The function of the IMR is to select, import, cryopreserve, maintain, and distribute these important strains of mice to the research community. To improve their value for research, the IMR also undertakes genetic development of stocks, such as transferring mutant genes or transgenes to defined genetic backgrounds and combining transgenes and/or targeted mutations to create new mouse models for research. The function of the IMR is to: * select biomedically important stocks of transgenic, chemically induced, and targeted mutant mice * import these stocks into the Jackson Laboratory by rederivation procedures that rid them of any pathogens they might carry * cryopreserve embryos from these stocks to protect them against accidental loss and genetic contamination * backcross the mutation onto an inbred strain, if necessary * distribute them to the scientific community More than 1000 mutant stocks have been accepted by the IMR from 1992 through December 2006. Current holdings include models for research on cancer; breast cancer; immunological and inflammatory diseases; neurological diseases; behavioral, cardiovascular and heart diseases; developmental, metabolic and other diseases; reporter (e.g., GFP) and recombinase (e.g., cre/loxP) strains. About eight strains a month are being added to the IMR holdings. Research is being conducted on improved methods for assisted reproduction and speed congenic production. Most of the targeted mutants arrive on a mixed 129xC57BL/6 genetic background, and as many of these as possible are backcrossed onto an inbred strain (usually C57BL/6J). In addition, new mouse models are being created by intercrossing carriers of specific transgenes and/or targeted mutations. Simple sequence length polymorphism DNA markers are being used to characterize and evaluate differences between inbred strains, substrains, and embryonic stem cell lines.

Proper citation: Induced Mutant Resource (RRID:SCR_008366) Copy   

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http://www.oege.org/software/hwe-mr-calc.shtml

This portal leads to the Chi-sq Hardy-Weinberg equilibrium test calculator for biallelic markers (SNPs, indels etc), including analysis for ascertainment bias for dominant/recessive models (due to biological or technical causes.) The purpose of this web program is for estimating possible missingness and an approach to evaluating missingness under different genetic models. Mendelian randomization (MR) permits causal inference between exposures and a disease. It can be compared with randomized controlled trials. Whereas in a randomized controlled trial the randomization occurs at entry into the trial, in MR the randomization occurs during gamete formation and conception. Several factors, including time since conception and sampling variation, are relevant to the interpretation of an MR test. Particularly important is consideration of the missingness of genotypes that can be originated by chance, genotyping errors, or clinical ascertainment. Testing for Hardy-Weinberg equilibrium (HWE) is a genetic approach that permits evaluation of missingness. Through this tool, the authors demonstrate evidence of nonconformity with HWE in real data. They also perform simulations to characterize the sensitivity of HWE tests to missingness. Unresolved missingness could lead to a false rejection of causality in an MR investigation of trait-disease association. These results indicate that large-scale studies, very high quality genotyping data, and detailed knowledge of the life-course genetics of the alleles/genotypes studied will largely mitigate this risk. Sponsors: This resource is supported by an Intermediate Fellowship (grant FS/05/065/19497) from the British Heart Foundation.

Proper citation: Hardy-Weinberg Equilibrium Calculator (RRID:SCR_008371) Copy   

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https://www.drugabuse.gov/publications/drugfacts/genetics-epigenetics-addiction

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 17, 2013. An archived video on the web providing comprehensive and hands-on training in genetics and epigenetic methodology. The purpose of the course is to provide an introduction to approaches and tools for identifying genes that confer vulnerability to addiction and individual differences in responses to treatments. The course is targeted to those who are new to the field of addiction genetics. The course was held over 5 days with lectures and hands-on demonstrations given each day. Viewers of the course will gain familiarity with conceptual and practical approaches to complex disorders using relevant genetic and epigenetic databases, and appropriate statistical and empirical approaches. Topics covered Behavioral genetics, genetic epidemiology, twin and adoption studies, statistical genetic concepts and approaches for mapping complex traits, haplotype based approaches for association mapping, genome-wide scans for addictive disorders, application of linkage for mapping genes and genetic loci for addictive disorders, pharmacogenomics of treatment of addictive disorders, Baysian Methods for identifying gene-gene interactions, analysis of copy number variation, practical use of genetic databases, mapping of complex traits in mice, methods for analyzing gene expression, and methods for doing epigenetic analysis are covered. The course was held April 4, 2008, at the Bethesda North Marriott Hotel and Conference Center, 5701 Marinelli Road, Bethesda, MD 20852.

Proper citation: Short Course on the Genetics and Epigenetics of Addiction National Institute on Drug Abuse: Archived Video (RRID:SCR_002783) Copy   

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https://www.ddbj.nig.ac.jp/jga/index-e.html

A service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects. The JGA contains exclusive data collected from individuals whose consent agreements authorize data release only for specific research use or to bona fide researchers. Strict protocols govern how information is managed, stored and distributed by the JGA. Once processed, all data are encrypted. The JGA accepts only de-identified data approved by JST-NBDC. The JGA implements access-granting policy whereby the decisions of who will be granted access to the data resides with the JST-NBDC. After data submission the JGA team will process the data into databases and archive the original data files. The accepted data types include manufacturer-specific raw data formats from the array-based and new sequencing platforms. The processed data such as the genotype and structural variants or any summary level statistical analyses from the original study authors are stored in databases. The JGA also accepts and distributes any phenotype data associated with the samples. For other human biological data, please contact the NBDC human data ethical committee.

Proper citation: Japanese Genotype-phenotype Archive (JGA) (RRID:SCR_003118) Copy   

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http://www.genome.gov/Glossary/

Glossary of Genetic Terms to help everyone understand the terms and concepts used in genetic research. In addition to definitions, specialists in the field of genetics share their descriptions of terms, and many terms include images, animation and links to related terms.

Proper citation: Talking Glossary of Genetic Terms (RRID:SCR_003215) Copy   

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http://www.bioconductor.org/packages/release/bioc/html/CGEN.html

Software R package for analysis of case-control studies in genetic epidemiology.

Proper citation: CGEN (RRID:SCR_001251) Copy   

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http://www.morpholinodatabase.org/

Central database to house data on morpholino screens currently containing over 700 morpholinos including control and multiple morpholinos against the same target. A publicly accessible sequence-based search opens this database for morpholinos against a particular target for the zebrafish community. Morpholino Screens: They set out to identify all cotranslationally translocated genes in the zebrafish genome (Secretome/CTT-ome). Morpholinos were designed against putative secreted/CTT targets and injected into 1-4 cell stage zebrafish embryos. The embryos were observed over a 5 day period for defects in several different systems. The first screen examined 184 gene targets of which 26 demonstrated defects of interest (Pickart et al. 2006). A collaboration with the Verfaillie laboratory examined the knockdown of targets identified in a comparative microarray analysis of hematopoietic stem cells demonstrating how microarray and morpholino technologies can be used in conjunction to enrich for defects in specific developmental processes. Currently, many collaborations are underway to identify genes involved in morphological, kidney, skin, eye, pigment, vascular and hematopoietic development, lipid metabolism and more. The screen types referred to in the search functions are the specific areas of development that were examined during the various screens, which include behavior, general morphology, pigmentation, toxicity, Pax2 expression, and development of the craniofacial structures, eyes, kidneys, pituitary, and skin. Only data pertaining to specific tests performed are presented. Due to the complexity of this international collaboration and time constraints, not all morpholinos were subjected to all screen types. They are currently expanding public access to the database. In the future we will provide: * Mortality curves and dose range for each morpholino * Preliminary data regarding the effectiveness of each morpholino * Expanded annotation for each morpholino * External linkage of our morpholino sequences to ZFIN and Ensembl. To submit morpholino-knockdown results to MODB please contact the administrator for a user name and password.

Proper citation: Morpholino Database (RRID:SCR_001378) Copy   

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http://www.genome.jp/kegg/expression/

Database for mapping gene expression profiles to pathways and genomes. Repository of microarray gene expression profile data for Synechocystis PCC6803 (syn), Bacillus subtilis (bsu), Escherichia coli W3110 (ecj), Anabaena PCC7120 (ana), and other species contributed by the Japanese research community.

Proper citation: Kyoto Encyclopedia of Genes and Genomes Expression Database (RRID:SCR_001120) Copy   

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http://www.well.ox.ac.uk/happy/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software package for Multipoint QTL Mapping in Genetically Heterogeneous Animals (entry from Genetic Analysis Software) The method is implemented in a C-program and there is now an R version of HAPPY. You can run HAPPY remotely from their web server using your own data (or try it out on the data provided for download).

Proper citation: Happy (RRID:SCR_001395) Copy   

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http://neuronalarchitects.com/ibiofind.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 17, 2016. C#.NET 4.0 WPF / OWL / REST / JSON / SPARQL multi-threaded, parallel desktop application enables the construction of biomedical knowledge through PubMed, ScienceDirect, EndNote and NIH Grant repositories for tracking the work of medical researchers for ranking and recommendations. Users can crawl web sites, build latent semantic indices to generate literature searches for both Clinical Translation Science Award and non-CTSA institutions, examine publications, build Bayesian networks for neural correlates, gene to gene interactions, protein to protein interactions and as well drug treatment hypotheses. Furthermore, one can easily access potential researcher information, monitor and evolve their networks and search for possible collaborators and software tools for creating biomedical informatics products. The application is designed to work with the ModelMaker, R, Neural Maestro, Lucene, EndNote and MindGenius applications to improve the quality and quantity of medical research. iBIOFind interfaces with both eNeoTutor and ModelMaker 2013 Web Services Implementation in .NET for eNeoTutor to aid instructors to build neuroscience courses as well as rare diseases. Added: Rare Disease Explorer: The Visualization of Rare Disease, Gene and Protein Networks application module. Cinematics for the Image Finder from Yale. The ability to automatically generate and update websites for rare diseases. Cytoscape integration for the construction and visualization of pathways for Molecular targets of Model Organisms. Productivity metrics for medical researchers in rare diseases. iBIOFind 2013 database now includes over 150 medical schools in the US along with Clinical Translational Science Award Institutions for the generation of biomedical knowledge, biomedical informatics and Researcher Profiles.

Proper citation: iBIOFind (RRID:SCR_001587) Copy   

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http://www.norcomm.org/index.htm

Large-scale research initiative focused on developing and distributing a library of mouse embryonic stem (ES) cell lines carrying single gene trapped or targeted mutations across the mouse genome. NorCOMM's large and growing archive of ES cells is publicly available on a cost-recovery basis from the Canadian Mouse Mutant Repository. As an international public resource, access to clones is unrestricted and nonexclusive. Through NorCOMM's affiliation with the Canadian Mouse Consortium (CMC), NorCOMM also provides clients with a single point of access to regional mouse derivation, phenotyping, genetic and archiving services across Canada. These value-added services can help your company harness NorCOMM's resources for drug discovery, target discovery and preclinical validation.

Proper citation: North American Conditional Mouse Mutagenesis Project (RRID:SCR_001614) Copy   

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Issue

http://www.nitrc.org/projects/plink

Open source whole genome association analysis toolset, designed to perform range of basic, large scale analyses in computationally efficient manner. Used for analysis of genotype/phenotype data. Through integration with gPLINK and Haploview, there is some support for subsequent visualization, annotation and storage of results. PLINK 1.9 is improved and second generation of the software.

Proper citation: PLINK (RRID:SCR_001757) Copy   

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http://icahn.mssm.edu/research/resources/shared-resource-facilities/in-vivo-molecular-imaging

The In-Vivo Molecular Imaging Laboratory (IMIL) is a MSSM shared resource facility serving the research community of Mount Sinai with equipment and imaging expertise. State-of-the-art bioluminescent as well as fluorescent imaging modalities are supported for in-vivo monitoring of cellular and genetic activity. Investigators are provided with cutting edge imaging technologies as well as analysis techniques. The long-term goal is to establish a comprehensive SRF for in-vivo molecular imaging using micro-MRI, micro-PET and other modalities. IMIL houses a Xenogen IVIS-200 Series imaging system with the integrated fluorescent imaging options. Simultaneous dual reporter in-vivo imaging is possible with bioluminescence and fluorescence probes. The imaging chamber has a gas anesthesia manifold that can accommodate up to 5 mice for simultaneously image acquisition. Selectable field of views allow in-plane (X,Y) imaging resolutions of up to 60-microm. Integrated spectra filters allow for the determination of signal source depth (Z). IMIL will provide data acquisition services as well as analysis. IMIL has a dedicated imaging technologist for data acquisition. Investigators will bring their prepared animal to the lab and an IMIL imaging technologist will assist in sedating the animals and acquire imaging data. Typical imaging sessions last about an hour. Certified users who are trained in the use of the software will be able to perform their own analysis at the console. Usage of the imaging device is charged by the hour ($100/hour). Structural Imaging The IVIS-200 has the built-in capability of obtaining an image of the surface topography of the animal for 2D and 3D localization. If additional true 3D imaging data is required, micro MRI is available through the Imaging Science Laboratories (ISL). Image Analysis The IVIS-200 has an integrated image acquisition and analysis software (Living Image Software 2.50). Comprehensive data quantification is possible with this software. Raw data as well as analyzed results can be electronically transferred to the investigators. Support is also available for additional image analysis such as intermodality coregistration, 3D rendering, and group statistics. Additional software packages include MedX, SPM, Brainvoyager, Analyze, and in-house developed software.

Proper citation: Mount Sinai School of Medicine: In-Vivo Molecular Imaging Laboratory (RRID:SCR_001785) Copy   

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https://www.snpstats.net/

A web-based application designed from a genetic epidemiology point of view to analyze association studies using single nucleotide polymorphisms (SNPs). For each selected SNP, you will receive: * Allele and genotype frequencies * Test for Hardy-Weinberg equilibrium * Analysis of association with a response variable based on linear or logistic regression * Multiple inheritance models: co-dominant, dominant, recessive, over-dominant and additive * Analysis of interactions (gene-gene or gene-environment) If multiple SNPs are selected: * Linkage disequilibrium statistics * Haplotype frequency estimation * Analysis of association of haplotypes with the response * Analysis of interactions (haplotypes-covariate)

Proper citation: SNPSTATS (RRID:SCR_002142) Copy   

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http://ftp://ftp.ncbi.nlm.nih.gov/pub/mhc/rbc/Final Archive

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 23, 2019.BGMUT was database that provided publicly accessible platform for DNA sequences and curated set of blood mutation information. Data Archive are available at ftp://ftp.ncbi.nlm.nih.gov/pub/mhc/rbc/Final Archive.

Proper citation: Blood Group Antigen Gene Mutation Database (RRID:SCR_002297) Copy   

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